CN115009288A - Method and device for determining vehicle weight - Google Patents

Method and device for determining vehicle weight Download PDF

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Publication number
CN115009288A
CN115009288A CN202210847294.6A CN202210847294A CN115009288A CN 115009288 A CN115009288 A CN 115009288A CN 202210847294 A CN202210847294 A CN 202210847294A CN 115009288 A CN115009288 A CN 115009288A
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China
Prior art keywords
vehicle
state data
torque
speed
weight
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CN202210847294.6A
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Inventor
王祥
冯彦明
张宗英
赵祥博
赵建永
刘通
王振
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Weichai Power Co Ltd
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Weichai Power Co Ltd
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Priority to CN202210847294.6A priority Critical patent/CN115009288A/en
Publication of CN115009288A publication Critical patent/CN115009288A/en
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/12—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to parameters of the vehicle itself, e.g. tyre models
    • B60W40/13—Load or weight
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0019—Control system elements or transfer functions
    • B60W2050/0028—Mathematical models, e.g. for simulation
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0001—Details of the control system
    • B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2400/00—Indexing codes relating to detected, measured or calculated conditions or factors
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/06—Combustion engines, Gas turbines
    • B60W2510/0604—Throttle position
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/06—Combustion engines, Gas turbines
    • B60W2510/0638—Engine speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2510/00—Input parameters relating to a particular sub-units
    • B60W2510/06—Combustion engines, Gas turbines
    • B60W2510/0657—Engine torque
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • B60W2520/105—Longitudinal acceleration
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/12—Lateral speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/12—Lateral speed
    • B60W2520/125—Lateral acceleration
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2555/00—Input parameters relating to exterior conditions, not covered by groups B60W2552/00, B60W2554/00
    • B60W2555/20—Ambient conditions, e.g. wind or rain
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/80—Technologies aiming to reduce greenhouse gasses emissions common to all road transportation technologies
    • Y02T10/84—Data processing systems or methods, management, administration

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Human Computer Interaction (AREA)
  • Combined Controls Of Internal Combustion Engines (AREA)

Abstract

The application provides a method and a device for determining the weight of a vehicle, wherein the method comprises the following steps: obtaining a vehicle state data sequence of a vehicle in a driving process, wherein the vehicle state data sequence comprises: vehicle state data at a plurality of different acquisition moments; determining at least one target time interval in which the vehicle running state meets a set condition based on the vehicle state data at a plurality of different acquisition moments in the vehicle state data sequence, wherein the target time interval comprises a plurality of continuous acquisition moments, and the condition that the vehicle running state meets the set condition represents that the vehicle is in a running state of uniform speed or uniform acceleration; and determining the vehicle weight of the vehicle based on the vehicle state data in the target time interval and the vehicle longitudinal dynamic model. The scheme of this application can realize confirming vehicle weight more accurately.

Description

Method and device for determining vehicle weight
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a method and an apparatus for determining a vehicle weight.
Background
The internet of vehicles means that sensors and the like on the vehicles are used for sensing vehicle state information of the vehicles, and intelligent management of traffic, provision of different functional services for the vehicles, intelligent control of the vehicles and the like are realized by means of a communication network and an information processing technology. In big data analysis applications based on the internet of vehicles, determining the weight of a vehicle plays an important role in analyzing the operation condition of the vehicle and the like.
However, it is difficult to measure the weight of the vehicle during the driving process, and therefore, how to accurately determine the weight of the vehicle is a technical problem that needs to be solved by those skilled in the art.
Disclosure of Invention
The application provides a method and a device for determining the weight of a vehicle, so as to determine the weight of the vehicle more accurately.
In one aspect, the present application provides a method of determining a weight of a vehicle, comprising:
obtaining a vehicle state data sequence of a vehicle during driving, wherein the vehicle state data sequence comprises: vehicle state data at a plurality of different acquisition moments;
determining at least one target time interval in which the vehicle running state meets a set condition based on the vehicle state data at a plurality of different acquisition moments in the vehicle state data sequence, wherein the target time interval comprises a plurality of continuous acquisition moments, and the vehicle running state meeting the set condition represents that the vehicle is in a running state of uniform speed or uniform acceleration;
and determining the vehicle weight of the vehicle by combining a vehicle longitudinal dynamic model based on each vehicle state data in the target time interval.
In one possible implementation, the vehicle state data includes: a vehicle speed, acceleration, and torque of the vehicle;
the vehicle running state satisfies a set condition, and includes:
the vehicle running state satisfies a first set condition including: the variation of the vehicle speed is smaller than a vehicle speed variation threshold, and the variation of the torque is smaller than a first torque threshold;
alternatively, the first and second electrodes may be,
the vehicle running state satisfies a second set condition including: the acceleration of the vehicle is greater than an acceleration threshold, the variation of the acceleration is less than an acceleration variation threshold, the variation of the torque is greater than a second torque threshold, and the variation of the torque is less than a third torque threshold.
In yet another possible implementation, the vehicle state data further includes: the atmospheric pressure of the vehicle, the accelerator pedal opening of the vehicle, and the engine speed of the vehicle;
the first setting condition further includes at least one of:
the atmospheric pressure of the vehicle is unchanged;
the opening degree of an accelerator pedal of the vehicle is greater than a first opening degree value;
the variation of the non-transmission impact value of the vehicle is smaller than a first transmission impact threshold value, and the non-transmission impact value is the ratio of the engine speed of the vehicle to the vehicle speed of the vehicle;
the second setting condition further includes at least one of:
the atmospheric pressure of the vehicle is unchanged;
the opening degree of an accelerator pedal of the vehicle is greater than a second opening degree value;
the variation of the gearless impact value of the vehicle is less than a second transmission impact threshold value.
In yet another possible implementation, the vehicle state data includes: the speed, acceleration, torque and engine speed of the vehicle;
determining the vehicle weight of the vehicle based on the vehicle state data in the target time interval and by combining a vehicle longitudinal dynamics model, wherein the determining comprises the following steps:
determining a vehicle speed average value of the vehicle speed, an acceleration average value of the acceleration, a torque average value of the torque and a rotating speed average value of the engine rotating speed in the target time interval based on vehicle state data at different acquisition moments in the target time interval;
determining a vehicle weight of the vehicle in conjunction with a vehicle longitudinal dynamics model based on the vehicle speed average, the acceleration average, the torque average, and the rotational speed average.
In another possible implementation manner, after determining the vehicle weight of the vehicle based on each vehicle state data in the target time interval and in combination with a vehicle longitudinal dynamics model, the method further includes:
rejecting abnormal values of the vehicle weight in the vehicle weight corresponding to the at least one target time interval to obtain at least one vehicle weight after the abnormal values are rejected;
and determining the average value of at least one vehicle weight after the abnormal value is eliminated as the vehicle weight of the vehicle in the running process.
In another possible implementation manner, the rejecting the abnormal vehicle weight value in the vehicle weight corresponding to the at least one target time interval includes:
calculating the standard deviation of the vehicle weight corresponding to the at least one target time interval, and eliminating the vehicle weight exceeding the set multiple of the standard deviation;
alternatively, the first and second liquid crystal display panels may be,
determining a sorting sequence of the vehicle weights corresponding to the at least one target time interval according to the sequence of the vehicle weights from small to large, dividing the vehicle weights corresponding to the at least one target time interval into N parts based on the sorting sequence, and rejecting the vehicle weights which are positioned at the most front 1/N and the most rear 1/N in the sorting sequence, wherein N is a set natural number which is larger than 2.
In yet another possible implementation manner, the obtaining a vehicle state data sequence of the vehicle during driving includes:
acquiring a vehicle data total sequence of the collected vehicle, wherein the vehicle data total sequence comprises a plurality of vehicle state data at different moments, and the vehicle state data comprises the speed of the vehicle;
and extracting at least one section of vehicle state data sequence representing the vehicle in the driving process from the vehicle data total sequence based on the vehicle speed characteristic of the vehicle.
In yet another aspect, the present application further provides an apparatus for determining a weight of a vehicle, comprising:
a data obtaining unit configured to obtain a vehicle state data sequence of a vehicle during traveling, the vehicle state data sequence including: vehicle state data at a plurality of different acquisition moments;
the interval determining unit is used for determining at least one target time interval in which the vehicle running state meets a set condition based on the vehicle state data at a plurality of different acquisition moments in the vehicle state data sequence, wherein the target time interval comprises a plurality of continuous acquisition moments, and the vehicle running state meeting the set condition represents that the vehicle is in a running state of uniform speed or uniform acceleration;
and the weight determining unit is used for determining the vehicle weight of the vehicle by combining a vehicle longitudinal dynamic model based on each vehicle state data in the target time interval.
In still another possible implementation manner, the vehicle state data obtained by the data obtaining unit includes: a vehicle speed, acceleration, and torque of the vehicle;
the section determination unit, in which the vehicle running state satisfies a set condition, includes:
the vehicle running state satisfies a first set condition including: the variation of the vehicle speed is smaller than a vehicle speed variation threshold, and the variation of the torque is smaller than a first torque threshold;
alternatively, the first and second electrodes may be,
the vehicle running state satisfies a second set condition including: the acceleration of the vehicle is greater than an acceleration threshold, the variation of the acceleration is less than an acceleration variation threshold, the variation of the torque is greater than a second torque threshold, and the variation of the torque is less than a third torque threshold.
In yet another possible implementation manner, the vehicle state data obtained by the data obtaining unit further includes: the atmospheric pressure of the vehicle, the accelerator pedal opening of the vehicle, and the engine speed of the vehicle;
the first setting condition further includes at least one of:
the atmospheric pressure of the vehicle is unchanged;
the opening degree of an accelerator pedal of the vehicle is greater than a first opening degree value;
the variation of the non-transmission impact value of the vehicle is smaller than a first transmission impact threshold value, and the non-transmission impact value is the ratio of the engine speed of the vehicle to the vehicle speed of the vehicle;
the second setting condition further includes at least one of:
the atmospheric pressure of the vehicle is unchanged;
the opening degree of an accelerator pedal of the vehicle is greater than a second opening degree value;
the variation of the gearless impact value of the vehicle is less than a second transmission impact threshold value.
As can be seen from the above, in the embodiment of the present application, after the vehicle state data sequence of the vehicle in the driving process is obtained, the target time interval in which the vehicle driving state meets the set condition is determined based on the vehicle state data at a plurality of different collection times in the vehicle state sequence. The vehicle running state meets the condition that the set bar represents that the vehicle is in a running state of constant speed or uniform acceleration, and the torque of the vehicle in the running state is relatively stable, so that the difference between the torque reported at a certain collection moment and the real torque caused by rapid change of the torque can be reduced, and the condition that the torque in the vehicle state data at the collection moment is not matched with other data can be reduced, therefore, the vehicle weight of the vehicle is determined based on each vehicle state data in the target time period, the condition that the calculated vehicle weight is inaccurate due to the fact that the torque in the vehicle state data is not matched with other data in the vehicle state data can be reduced, and the accuracy of determining the vehicle weight can be improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on the provided drawings without creative efforts.
FIG. 1 is a schematic flow chart diagram illustrating a method for determining vehicle weight provided by an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating a method for determining vehicle weight provided by an embodiment of the present application;
fig. 3 is a schematic structural diagram illustrating a component of the apparatus for determining the weight of a vehicle according to the embodiment of the present application.
Detailed Description
The scheme of the embodiment of the application is suitable for determining the weight of the vehicle based on the vehicle state data in the vehicle running process, so that the weight of the vehicle can be accurately determined under the vehicle running state.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without inventive step, are within the scope of the present disclosure.
As shown in fig. 1, which shows a schematic flowchart of a method for determining a vehicle weight according to the present invention, the method of the present embodiment may be applied to a data processing platform of an internet of vehicles, and may also be applied to a vehicle-mounted terminal for collecting vehicle status data in a vehicle, which is not limited in this regard.
The method of the embodiment may include:
s101, obtaining a vehicle state data sequence of the vehicle in the running process.
Wherein the vehicle state data sequence comprises: vehicle state data at a plurality of different collection times.
The vehicle state data refers to data related to the vehicle running state during the vehicle running process, which is obtained by various sensors through an on-board terminal on the vehicle. For example, the vehicle state data may include data streams related to the vehicle engine and related data for diagnostic information required by the on-board automatic diagnostic system, and the like.
For example, the vehicle state data may include part or all of data such as a vehicle speed, an acceleration, a torque (also referred to as an engine torque), and an engine speed of the vehicle.
It can be understood that the weight of the vehicle can be measured by a specific vehicle weighing device in a scene that the vehicle is at a standstill and the like, and the vehicle weight can be determined without adopting the scheme of the application since some regulations on the operation of the vehicle are not involved. Based on the situation, the scheme of the application is suitable for determining the weight scene of the vehicle based on the vehicle state data collected in the driving process of the vehicle.
It is understood that the vehicle-mounted terminal on the vehicle collects the vehicle state data according to the set sampling frequency, for example, the vehicle-mounted terminal may be a remote terminal meeting the set standard (for example, meeting the national sixth-stage vehicle pollutant emission standard, i.e., the national sixth standard), and therefore the sampling frequency of the vehicle-mounted terminal is generally lower than 1 HZ. For the sake of distinction, the time at which the vehicle state data is collected is referred to as the collection time. Accordingly, the vehicle state data sequence is actually a time sequence which contains the vehicle state data acquired by the vehicle-mounted terminal at a plurality of acquisition moments.
It can be understood that the vehicle-mounted terminal may continuously collect vehicle state data of the vehicle and report the vehicle state data to the vehicle networking data processing platform, and on this basis, the vehicle state data that the vehicle-mounted terminal or the vehicle networking data processing platform may obtain may include not only the vehicle state data of the vehicle during traveling, but also the vehicle state data of the vehicle in a scenario of loading or unloading the vehicle.
Based on the method, a vehicle data total sequence of the collected vehicle is obtained at the vehicle networking data processing platform or the vehicle-mounted terminal, the vehicle data total sequence comprises vehicle state data of a plurality of different moments, and the vehicle state data comprises the vehicle speed of the vehicle. On the basis of the vehicle speed characteristics, at least one section of vehicle state data sequence which is used for representing the vehicle in the driving process can be extracted from the vehicle data total sequence. If the vehicle is in a running state, the process that the vehicle gradually increases from zero speed is necessarily involved, or a vehicle running process that the vehicle gradually increases from zero speed to zero speed and finally returns to zero speed is included, and on the basis of the process, the vehicle state data sequence of the vehicle in the running state can be determined by analyzing the vehicle speed of the vehicle.
S102, determining at least one target time interval in which the vehicle running state meets set conditions based on the vehicle state data of a plurality of different collection moments in the vehicle state data sequence.
The running state of the vehicle meets the set conditions and represents that the vehicle is in a running state of constant speed or uniform acceleration.
It can be understood that, when the vehicle is in a running state of uniform speed or uniform acceleration, the vehicle runs more smoothly, so that the torque of the engine in the vehicle is also in a more stable state, and a state of rapid change of the torque cannot occur. Based on this, the fact that the vehicle running state satisfies the set condition may also indicate that the amount of change in the torque of the vehicle is smaller than the set threshold, that is, the torque of the vehicle is in a steady state.
In the present application, the vehicle running state may be obtained by the variation of the vehicle speed, acceleration and torque of the vehicle, and in practical applications, the specific situation that the vehicle running state satisfies the setting condition may be set as required, which is not limited to this.
Wherein the target time interval comprises a plurality of consecutive acquisition moments. The target time interval is a part of the total time interval covered by each vehicle state data in the vehicle state data sequence. For example, if a vehicle state data series is obtained over 1 hour, then the target time interval may be a continuous time interval having a duration of less than one hour.
It is understood that there may be one or more periods of stationary operation in which the vehicle is at a constant speed or at a uniform acceleration during the total time interval corresponding to the vehicle state data sequence, and each of the periods may be regarded as a target time interval.
It is understood that the duration of different target time intervals may be different in the present application, since the duration of each smooth operation may also be different during the driving of the vehicle. Of course, in practical application, the duration of the target time interval may also be set as needed, and at least one target time interval satisfying the condition is selected.
And S103, determining the vehicle weight of the vehicle by combining the vehicle longitudinal dynamic model based on the vehicle state data in the target time interval.
The vehicle longitudinal dynamic model is also called as an automobile longitudinal dynamic model and is used for describing the balance relation among various external forces acting on an automobile along the driving direction of the automobile, and the weight of the automobile can be calculated by combining the balance relation among acting forces such as driving force, air resistance, rolling friction resistance, gradient resistance and the like in the driving process of the automobile due to the fact that the weight of the automobile is involved in the vehicle longitudinal dynamic model.
Under the condition that the vehicle state data at different sampling moments in the target time interval are determined, the method and the device do not limit the specific process of calculating the vehicle weight by combining the vehicle longitudinal dynamic model.
The inventors of the present application have found that: the vehicle weight of the vehicle can be calculated by directly utilizing the acquired vehicle state data and combining a vehicle dynamic model, but the calculated vehicle weight has larger deviation and lower accuracy.
The inventor finds out through further research that: if the sampling frequency of the vehicle state data of the vehicle is high, the accuracy of the determined vehicle weight is relatively high on the basis of the collected vehicle state data and the vehicle longitudinal dynamic model; however, if the sampling frequency of the vehicle state data of the vehicle is low, the error of the vehicle weight calculated in conjunction with the vehicle longitudinal dynamics model is large. And under the condition of adopting a lower sampling frequency to collect the vehicle state data, the error of the calculated vehicle weight is caused to be larger because: because the torque of the engine of the vehicle changes rapidly, under the condition of low sampling frequency, the torque of the engine collected at a certain sampling moment may be different from the true value of the torque at the current moment, so that the collected torque and other vehicle state data such as the currently collected vehicle speed and acceleration are not data corresponding to the same moment, and the calculated vehicle weight is wrong due to the fact that errors exist in the torque or the torque is not matched with the data such as the vehicle speed in the vehicle state data.
In the application, the vehicle is in a steady operation state of uniform speed or uniform acceleration in the target time interval, the torque of an engine of the vehicle is relatively stable, and the situation of rapid change of the torque cannot occur, so that even if the sampling frequency of the vehicle state data is relatively low, the situation that the torque acquired at the moment and the real torque are deviated due to rapid change of the torque cannot occur, so that the data of the vehicle speed, the acceleration and the like in the acquired vehicle state data and the torque in the vehicle state data do not belong to the data at the same moment is avoided, namely, the situation that the data of the vehicle speed, the acceleration and the like in the vehicle state data are not matched with the torque is reduced.
As can be seen from the above, in the embodiment of the present application, after the vehicle state data sequence of the vehicle in the driving process is obtained, the target time interval in which the vehicle driving state meets the set condition is determined based on the vehicle state data at a plurality of different collection times in the vehicle state sequence. The vehicle running state meets the condition that the set bar represents that the vehicle is in a running state of constant speed or uniform acceleration, and the torque of the vehicle in the running state is relatively stable, so that the difference between the torque reported at a certain collection moment and the real torque caused by rapid change of the torque can be reduced, and the condition that the torque in the vehicle state data at the collection moment is not matched with other data can be reduced, therefore, the vehicle weight of the vehicle is determined based on each vehicle state data in the target time period, the condition that the calculated vehicle weight is inaccurate due to the fact that the torque in the vehicle state data is not matched with other data in the vehicle state data can be reduced, and the accuracy of determining the vehicle weight can be improved.
It is to be understood that there are many possible setting conditions for determining whether the vehicle is in the constant speed or the uniform acceleration driving state in the present application, and the following description is made in conjunction with one possible implementation manner.
As shown in fig. 2, which shows another schematic flowchart of the method for determining the weight of the vehicle provided in the embodiment of the present application, the method of the present embodiment may include:
s201, obtaining a vehicle state data sequence of the vehicle in the running process.
Wherein the vehicle state data sequence comprises: vehicle state data at a plurality of different collection times.
In the embodiment of the present application, the vehicle state data includes at least a vehicle speed, an acceleration, and a torque of the vehicle.
S202, determining at least one target time interval in which the vehicle running state meets a first set condition or a second set condition based on the vehicle state data of a plurality of different collection moments in the vehicle state data sequence.
The vehicle running state meets the first set condition, the vehicle is represented to be in a constant speed running state, and the torque of the vehicle is stable. Wherein the vehicle running state satisfying the first set condition includes: the amount of change in vehicle speed is less than a vehicle speed change threshold and the amount of change in torque is less than a first torque threshold. The vehicle speed change threshold and the first torque threshold may be set as desired.
The variation of the vehicle speed is smaller than the vehicle speed variation threshold, which may be that a difference between the vehicle speeds at any two adjacent acquisition times (within the target time interval) is smaller than the vehicle speed variation threshold, so that the difference between the maximum value and the minimum value of the vehicle speed within the finally determined target time interval is smaller.
Similarly, the torque variation amount smaller than the first torque threshold may be that the difference between the torques at any two adjacent sampling times is smaller than the first torque variation amount, so that the maximum variation amount of the torque of the engine of the vehicle in the target time interval is smaller.
It can be understood that, when the vehicle is in a state of ascending or descending, even if the speed of the vehicle is relatively stable, the torque change of the vehicle may be affected, and therefore, in order to more reliably ensure that the vehicle is in a relatively stable uniform speed running state, the torque of the vehicle will not change greatly in a short time, the vehicle state data of the application may further include: the atmospheric pressure at which the vehicle is located. Correspondingly, the vehicle running state meeting the first set condition in the present application may further include: the atmospheric pressure at which the vehicle is located does not change.
If the atmospheric pressure of the vehicle in the target time interval is not changed, the altitude of the vehicle is not changed, the vehicle can be indicated to be in a gentle road section, and the special condition that the vehicle runs on a slope road is eliminated.
It is understood that if the vehicle is coasting due to neutral or no throttle, although the vehicle is in a constant speed running state, the torque of the engine of the vehicle may be zero, and thus the calculation of the vehicle weight may not be performed. Based on this, the vehicle state data in the present application may further include at least one of an accelerator pedal opening degree of the vehicle and an engine speed of the vehicle. Accordingly, the vehicle running state satisfying the first set condition may further include at least one of:
the opening degree of an accelerator pedal of the vehicle is greater than a first opening degree value;
the variation of the transmission-free impact value of the vehicle is smaller than the first transmission impact threshold value, wherein the transmission-free impact value is the ratio of the engine speed of the vehicle to the vehicle speed of the vehicle.
The ratio of the engine speed of the vehicle to the vehicle speed of the vehicle reflects the gear condition of the vehicle, and if the ratio is unchanged or the variation is smaller than a specific threshold, the gear of the vehicle can be regarded as being unchanged, so that the torque of the vehicle can be more reliably ensured to be in a stable state.
It is to be understood that, in practical applications, the first setting condition that the vehicle running state satisfies may be set as needed, in addition to the amount of change in the vehicle speed being smaller than the vehicle speed change threshold and the amount of change in the torque being smaller than the first torque threshold, including: the atmospheric pressure of the vehicle is unchanged, the opening degree of an accelerator pedal of the vehicle is larger than a first opening value, and the variation of the transmission-free impact value of the vehicle is smaller than a first transmission impact threshold value.
The vehicle running state meets a second set condition and represents that the vehicle is in a uniform acceleration running state, so that the torque of an engine of the vehicle is in a stable state, and the torque variation is small. Based on this, in the present application, the vehicle running state satisfying the second set condition may include: the acceleration of the vehicle is greater than the acceleration threshold, the variation of the acceleration is less than the acceleration variation threshold, the torque of the vehicle is greater than the second torque threshold, and the variation of the torque is less than the third torque threshold.
The acceleration threshold, the second torque threshold and the third torque threshold can be set according to requirements.
Similar to the first setting condition, in order to reduce the influence of the vehicle coasting due to a slope, neutral, or other reasons on the torque change or to make the torque zero, the vehicle driving state satisfying the second setting condition may further include at least one of:
the atmospheric pressure of the vehicle is unchanged;
the opening degree of an accelerator pedal of the vehicle is greater than a second opening degree value;
the variation of the no-transmission impact value of the vehicle is less than the second transmission impact threshold value.
It can be understood that, in practical application, the total time interval corresponding to the vehicle state data sequence may be analyzed segment by segment, each time interval in which the vehicle driving state meets the first setting condition or the second setting condition is finally extracted, and the extracted time interval is determined as the target time interval.
And S203, determining the vehicle weight of the vehicle by combining the vehicle longitudinal dynamic model based on the vehicle state data in the target time interval.
This step can be referred to the related description of the previous embodiment, and is not described herein again.
It can be understood that, in this embodiment, in order to determine the target time interval when the vehicle is in the steady operation state of uniform speed or uniform acceleration, not only the vehicle speed, the acceleration and the variation of the torque of the vehicle are considered, but also the atmospheric pressure, the accelerator pedal opening, the gear position and other conditions where the vehicle is located can be integrated, so that the target time interval when the vehicle is in the steady operation state can be selected more accurately and reliably, the torque variation of the vehicle in the target time interval is smaller, and the situation that the calculation of the vehicle weight is inaccurate due to the overlarge torque variation can be reduced.
It can be understood that some basic power parameters of the vehicle, such as the tire radius of the vehicle and the frontal area of the vehicle, are involved in the vehicle longitudinal dynamic model, and in the case that the model of the vehicle is fixed, the basic power parameters of the vehicle are fixed.
For ease of understanding, the process of calculating the vehicle weight of a vehicle in conjunction with a longitudinal vehicle dynamics model is described below in conjunction with an application scenario.
The vehicle longitudinal dynamics model can be expressed as the following formula one:
δma＝F t -F w -F f -F s (formula one);
wherein, delta is the whole vehicle rotational inertia of the vehicle, m is the vehicle weight (unit: kg) of the vehicle, and a is the acceleration of the vehicle.
F t For the driving force of the engine transmitted to the wheels, F w As air resistance, F f As rolling friction resistance, F s Is the slope resistance.
Wherein the driving force F t Can be expressed as the following formula two:
Figure BDA0003753350220000121
wherein T is a torque of an engine of the vehicle; i all right angle t Total speed ratio of the drive train, eta t For driveline efficiency, R is the tire radius.
Air resistance F w Can be expressed as the following formula three:
Figure BDA0003753350220000122
wherein C is the air resistance coefficient, A is the frontal area of the automobile, and u is the speed (unit: km/h).
Wherein the rolling friction resistance F f Can be expressed as the following equation four:
F f mgfcos α (formula four);
wherein g is the acceleration of gravity and alpha is the road slope angle.
Meanwhile, as can be known from the theory of the vehicle, when the power train is engaged, the relationship between the engine speed and the vehicle speed of the vehicle satisfies the following formula five:
Figure BDA0003753350220000131
wherein n is the engine speed.
In the formulas, the total rotational inertia of the vehicle, the total speed ratio of the transmission system, the efficiency of the transmission system and the coefficient of air resistance are all set default values, and the values of the parameters can be predetermined by combining the vehicle type. The automobile windward area and the tire radius of the vehicle belong to basic power parameters of the vehicle and can be obtained based on the type of the vehicle.
Based on the above five formulas, the vehicle weight of the vehicle can be derived and calculated.
Particularly, under the condition that the driving state of the vehicle meets the set condition, if the atmospheric pressure of the vehicle is set to be unchanged, the altitude of the vehicle is not changed, and the situation shows that the vehicle is not in an uphill or downhill state in the target time interval. On the basis, the following formula six can be obtained by combining the above five formulas:
Figure BDA0003753350220000132
and calculating the vehicle weight of the vehicle by using the formula six and combining the vehicle speed, the acceleration and the torque in the vehicle state data in the target time interval, the determined air resistance coefficient, the frontal area of the vehicle, the rolling friction encouraging coefficient, the power train efficiency and the like of the vehicle.
It can be understood that the target time interval includes vehicle state data at a plurality of different sampling moments, so that when calculating the vehicle weight, the vehicle state data at any one sampling moment in the target time interval can be selected to calculate the vehicle weight of the vehicle.
In a possible implementation manner, in order to further improve the accuracy of the determined vehicle weight, the application may further calculate the vehicle weight of the vehicle by combining the average value of each vehicle state data in the target time interval and the aforementioned vehicle longitudinal dynamics model.
Specifically, the vehicle state data includes at least: the vehicle speed, acceleration, torque, and engine speed of the vehicle. Correspondingly, the vehicle speed average value, the acceleration average value of the acceleration, the torque average value of the torque and the rotating speed average value of the engine rotating speed in the target time interval are determined based on the vehicle state data at different acquisition moments in the target time interval. On the basis of the vehicle speed average value, the acceleration average value, the torque average value and the rotating speed average value, the vehicle weight of the vehicle is determined by combining a vehicle longitudinal dynamic model.
For example, the vehicle weight of the vehicle can be calculated by substituting the vehicle speed average value, the acceleration average value, the torque average value, and the rotation speed average value into the above equation six.
It can be understood that, since a plurality of determined target time intervals may be provided, in order to make the accuracy of the finally determined vehicle weight higher, the present application may determine, for each target time interval, a vehicle weight based on the vehicle state data of the target time interval, so as to finally obtain at least one vehicle weight. On the basis, the application can calculate the average value of the at least one vehicle weight and determine the vehicle weight as the final vehicle weight of the vehicle.
Further, considering that an abnormal value may exist in at least one vehicle weight, the abnormal value in at least one vehicle weight may be removed by a statistical method. Namely, the vehicle weight abnormal value in the vehicle weight corresponding to the at least one target time interval is removed, and at least one vehicle weight after the abnormal value is removed is obtained. Accordingly, the average value of at least one vehicle weight after the elimination of the abnormal value may be determined as the vehicle weight of the vehicle during running.
The manner of rejecting the abnormal value of the vehicle weight corresponding to at least one target time interval of the vehicle may be multiple possibilities, and the following description will be made in combination with the two manners.
For example, in one possible implementation, the outlier rejection may be performed based on the standard deviation, specifically, the standard deviation of the vehicle weight corresponding to the at least one target time interval may be calculated, and the vehicle weight exceeding the set multiple of the standard deviation may be rejected. For example, the standard deviation of the at least one vehicle weight corresponding to the at least one target time interval may be calculated as an average of the at least one vehicle weight, and then an average of distances of the vehicle weight from the average may be calculated to obtain the standard deviation. The setting multiple can be set according to needs, for example, the setting multiple can be 3 times.
In yet another possible implementation, the abnormal vehicle weight may be rejected in combination with the N-quantile spacing method. The value of N may be a natural number greater than 2, for example, the value of N may be 4. Specifically, the sorting order of the vehicle weights corresponding to the at least one target time interval may be determined in the order from the smaller vehicle weight to the larger vehicle weight, the vehicle weights corresponding to the at least one target time interval are divided into N parts based on the sorting order, and the vehicle weights at the top 1/N and the bottom 1/N in the sorting order are removed.
Of course, the manner of rejecting the abnormal value in the at least one vehicle weight by other manners is also applicable to the present embodiment, and is not limited thereto.
The application also provides a device for determining the weight of the vehicle, which corresponds to the method for determining the weight of the vehicle. As shown in fig. 3, it shows a schematic structural diagram of an apparatus for determining vehicle weight according to an embodiment of the present application, and the apparatus may include:
a data obtaining unit 301, configured to obtain a vehicle state data sequence of a vehicle during driving, where the vehicle state data sequence includes: vehicle state data at a plurality of different acquisition moments;
an interval determining unit 302, configured to determine, based on vehicle state data at a plurality of different collection times in the vehicle state data sequence, at least one target time interval in which a vehicle driving state meets a set condition, where the target time interval includes a plurality of continuous collection times, and the vehicle driving state meeting the set condition indicates that the vehicle is in a driving state of uniform speed or uniform acceleration;
a weight determining unit 303, configured to determine a vehicle weight of the vehicle based on each vehicle state data in the target time interval in combination with a vehicle longitudinal dynamics model.
In one possible implementation, the vehicle state data obtained by the data obtaining unit includes: a vehicle speed, acceleration, and torque of the vehicle;
the section determination unit, in which the vehicle running state satisfies a set condition, includes:
the vehicle running state satisfies a first set condition including: the variation of the vehicle speed is smaller than a vehicle speed variation threshold, and the variation of the torque is smaller than a first torque threshold;
alternatively, the first and second electrodes may be,
the vehicle running state satisfies a second set condition including: the acceleration of the vehicle is greater than an acceleration threshold, the variation of the acceleration is less than an acceleration variation threshold, the variation of the torque is greater than a second torque threshold, and the variation of the torque is less than a third torque threshold.
In yet another possible implementation manner, the vehicle state data obtained by the data obtaining unit further includes: the atmospheric pressure of the vehicle, the accelerator pedal opening of the vehicle, and the engine speed of the vehicle;
the first setting condition further includes at least one of:
the atmospheric pressure of the vehicle is unchanged;
the opening degree of an accelerator pedal of the vehicle is greater than a first opening degree value;
the variation of the non-transmission impact value of the vehicle is smaller than a first transmission impact threshold value, and the non-transmission impact value is the ratio of the engine speed of the vehicle to the vehicle speed of the vehicle;
the second setting condition further includes at least one of:
the atmospheric pressure of the vehicle is unchanged;
the opening degree of an accelerator pedal of the vehicle is greater than a second opening degree value;
the variation of the gearless impact value of the vehicle is less than a second transmission impact threshold value.
In still another possible implementation, the vehicle state data obtained by the data obtaining unit includes: the speed, acceleration, torque and engine speed of the vehicle;
the weight determination unit includes:
the data averaging subunit is configured to determine, based on vehicle state data at different collection times in the target time interval, a vehicle speed average value of the vehicle speed, an acceleration average value of the acceleration, a torque average value of the torque, and a rotation speed average value of the engine rotation speed in the target time interval;
a weight determination subunit for determining a vehicle weight of the vehicle in conjunction with a vehicle longitudinal dynamics model based on the vehicle speed average, the acceleration average, the torque average, and the rotational speed average.
In yet another possible implementation manner, the apparatus further includes:
the data removing unit is used for removing the vehicle weight abnormal value in the vehicle weight corresponding to the at least one target time interval after the weight determining unit determines the vehicle weight of the vehicle, and obtaining at least one vehicle weight after the abnormal value is removed;
and a weight average unit for determining an average value of at least one vehicle weight after the elimination of the abnormal value as a vehicle weight of the vehicle during running.
In another possible implementation manner, the data culling unit includes:
the first data removing unit is used for calculating the standard deviation of the vehicle weight corresponding to the at least one target time interval and removing the vehicle weight exceeding the set multiple of the standard deviation;
alternatively, the first and second electrodes may be,
and the second data rejection unit is used for determining a sorting sequence of the vehicle weights corresponding to the at least one target time interval according to the sequence of the vehicle weights from small to large, dividing the vehicle weights corresponding to the at least one target time interval into N parts based on the sorting sequence, rejecting the vehicle weights at the most front 1/N and the most rear 1/N in the sorting sequence, wherein N is a set natural number greater than 2.
In yet another possible implementation manner, the data obtaining unit includes:
the system comprises an initial data obtaining unit, a data processing unit and a data processing unit, wherein the initial data obtaining unit is used for obtaining a vehicle data total sequence of collected vehicles, the vehicle data total sequence comprises a plurality of vehicle state data at different moments, and the vehicle state data comprises the vehicle speed of the vehicles;
and the data extraction unit is used for extracting at least one section of vehicle state data sequence representing the vehicle in the driving process from the vehicle data total sequence based on the vehicle speed characteristics of the vehicle.
It should be noted that, in the present specification, the embodiments are all described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments may be referred to each other. Meanwhile, the features described in the embodiments of the present specification may be replaced or combined with each other, so that those skilled in the art can implement or use the present application. For the device-like embodiment, since it is basically similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, 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 an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. 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 application. Thus, the present application 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.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.

Claims (10)

1. A method of determining a weight of a vehicle, comprising:
obtaining a vehicle state data sequence of a vehicle during driving, wherein the vehicle state data sequence comprises: vehicle state data at a plurality of different acquisition moments;
determining at least one target time interval in which the vehicle running state meets a set condition based on the vehicle state data of a plurality of different acquisition moments in the vehicle state data sequence, wherein the target time interval comprises a plurality of continuous acquisition moments, and the vehicle running state meeting the set condition represents that the vehicle is in a running state of uniform speed or uniform acceleration;
and determining the vehicle weight of the vehicle by combining a vehicle longitudinal dynamic model based on each vehicle state data in the target time interval.
2. The method of claim 1, wherein the vehicle state data comprises: a vehicle speed, acceleration, and torque of the vehicle;
the vehicle running state satisfies a set condition, and includes:
the vehicle running state satisfies a first set condition including: the variation of the vehicle speed is smaller than a vehicle speed variation threshold, and the variation of the torque is smaller than a first torque threshold;
alternatively, the first and second electrodes may be,
the vehicle running state satisfies a second set condition including: the acceleration of the vehicle is greater than an acceleration threshold, the variation of the acceleration is less than an acceleration variation threshold, the variation of the torque is greater than a second torque threshold, and the variation of the torque is less than a third torque threshold.
3. The method of claim 2, wherein the vehicle state data further comprises: the atmospheric pressure of the vehicle, the accelerator pedal opening of the vehicle and the engine speed of the vehicle;
the first setting condition further includes at least one of:
the atmospheric pressure of the vehicle is unchanged;
the opening degree of an accelerator pedal of the vehicle is greater than a first opening degree value;
the variation of the non-transmission impact value of the vehicle is smaller than a first transmission impact threshold value, and the non-transmission impact value is the ratio of the engine speed of the vehicle to the vehicle speed of the vehicle;
the second setting condition further includes at least one of:
the atmospheric pressure of the vehicle is unchanged;
the opening degree of an accelerator pedal of the vehicle is greater than a second opening degree value;
the variation of the gearless impact value of the vehicle is less than a second transmission impact threshold value.
4. The method of claim 1, wherein the vehicle state data comprises: the speed, acceleration, torque and engine speed of the vehicle;
determining the vehicle weight of the vehicle based on the vehicle state data in the target time interval and by combining a vehicle longitudinal dynamics model, wherein the determining comprises the following steps:
determining a vehicle speed average value of the vehicle speed, an acceleration average value of the acceleration, a torque average value of the torque and a rotating speed average value of the engine rotating speed in the target time interval based on vehicle state data at different acquisition moments in the target time interval;
determining a vehicle weight of the vehicle in conjunction with a vehicle longitudinal dynamics model based on the vehicle speed average, the acceleration average, the torque average, and the rotational speed average.
5. The method of claim 1 or 4, further comprising, after said determining the vehicle weight of the vehicle based on the respective vehicle state data within the target time interval in conjunction with a vehicle longitudinal dynamics model:
rejecting abnormal values of the vehicle weight in the vehicle weight corresponding to the at least one target time interval to obtain at least one vehicle weight after the abnormal values are rejected;
and determining the average value of at least one vehicle weight after the abnormal value is eliminated as the vehicle weight of the vehicle in the running process.
6. The method according to claim 5, wherein the eliminating of the vehicle weight abnormal value in the vehicle weight corresponding to the at least one target time interval comprises:
calculating the standard deviation of the vehicle weight corresponding to the at least one target time interval, and eliminating the vehicle weight exceeding the set multiple of the standard deviation;
alternatively, the first and second electrodes may be,
determining a sorting sequence of the vehicle weights corresponding to the at least one target time interval according to the sequence of the vehicle weights from small to large, dividing the vehicle weights corresponding to the at least one target time interval into N parts based on the sorting sequence, and rejecting the vehicle weights which are positioned at the most front 1/N and the most rear 1/N in the sorting sequence, wherein N is a set natural number which is larger than 2.
7. The method of claim 1, wherein the obtaining a vehicle state data sequence of the vehicle during travel comprises:
acquiring a vehicle data total sequence of the collected vehicle, wherein the vehicle data total sequence comprises a plurality of vehicle state data at different moments, and the vehicle state data comprises the speed of the vehicle;
and extracting at least one section of vehicle state data sequence representing the vehicle in the driving process from the vehicle data total sequence based on the vehicle speed characteristic of the vehicle.
8. An apparatus for determining the weight of a vehicle, comprising:
a data obtaining unit configured to obtain a vehicle state data sequence of a vehicle during traveling, the vehicle state data sequence including: vehicle state data at a plurality of different acquisition moments;
the interval determining unit is used for determining at least one target time interval in which the vehicle running state meets a set condition based on the vehicle state data at a plurality of different acquisition moments in the vehicle state data sequence, wherein the target time interval comprises a plurality of continuous acquisition moments, and the vehicle running state meeting the set condition represents that the vehicle is in a running state of uniform speed or uniform acceleration;
and the weight determining unit is used for determining the vehicle weight of the vehicle by combining a vehicle longitudinal dynamic model based on each vehicle state data in the target time interval.
9. The apparatus according to claim 8, wherein the vehicle state data obtained by the data obtaining unit includes: a vehicle speed, acceleration, and torque of the vehicle;
the section determination unit, in which the vehicle running state satisfies a set condition, includes:
the vehicle running state satisfies a first set condition including: the variation of the vehicle speed is smaller than a vehicle speed variation threshold, and the variation of the torque is smaller than a first torque threshold;
alternatively, the first and second electrodes may be,
the vehicle running state satisfies a second set condition including: the acceleration of the vehicle is greater than an acceleration threshold, the variation of the acceleration is less than an acceleration variation threshold, the variation of the torque is greater than a second torque threshold, and the variation of the torque is less than a third torque threshold.
10. The apparatus according to claim 9, wherein the vehicle state data obtained by the data obtaining unit further includes: the atmospheric pressure of the vehicle, the accelerator pedal opening of the vehicle, and the engine speed of the vehicle;
the first setting condition further includes at least one of:
the atmospheric pressure of the vehicle is unchanged;
the opening degree of an accelerator pedal of the vehicle is greater than a first opening degree value;
the variation of the non-transmission impact value of the vehicle is smaller than a first transmission impact threshold value, and the non-transmission impact value is the ratio of the engine speed of the vehicle to the vehicle speed of the vehicle;
the second setting condition further includes at least one of:
the atmospheric pressure of the vehicle is unchanged;
the opening degree of an accelerator pedal of the vehicle is greater than a second opening degree value;
the variation of the gearless impact value of the vehicle is less than a second transmission impact threshold value.
CN202210847294.6A 2022-07-19 2022-07-19 Method and device for determining vehicle weight Pending CN115009288A (en)

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CN115204417B (en) * 2022-09-13 2022-12-27 鱼快创领智能科技(南京)有限公司 Vehicle weight prediction method and system based on ensemble learning and storage medium

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