CN114750765A - Method, device, equipment, medium and product for determining road spectrum data of vehicle - Google Patents
Method, device, equipment, medium and product for determining road spectrum data of vehicle Download PDFInfo
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- 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
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- 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
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Abstract
The invention discloses a method, a device, equipment, a medium and a product for determining road spectrum data of a vehicle. The method comprises the following steps: acquiring road spectrum data of a vehicle, and determining wheel driving force of the vehicle based on the road spectrum data, wherein the wheel driving force is positively correlated with a vehicle gear; segmenting a road spectrum of a vehicle to obtain a plurality of road spectrum segments; optimizing a resistance coefficient and a vehicle load in a vehicle dynamics formula corresponding to each road spectrum segment based on the wheel-side driving force, and determining a real vehicle load and a real road gradient in each road spectrum segment according to the optimized vehicle dynamics formula corresponding to each road spectrum segment; and adding the real vehicle load and the real road gradient in each road spectrum segment into the road spectrum data to obtain the final road spectrum data of the vehicle. With this method, road spectrum data including the true vehicle load and the true road gradient can be obtained without increasing the vehicle additional cost.
Description
Technical Field
The embodiment of the invention relates to the technical field of vehicles, in particular to a method, a device, equipment, a medium and a product for determining road spectrum data of a vehicle.
Background
With the improvement of vehicle intelligent degree and environmental protection regulation requirements, the vehicle is generally provided with an internet of vehicles data acquisition device for acquiring the real-time state of an engine, road spectrum data such as vehicle speed, rotating speed, torque and the like of various vehicles can be acquired, and then the vehicle can be evaluated and evaluated in scenes such as vehicle power economy, driving assistance of users, vehicle fault detection, subsequent development and improvement guidance and the like according to the road spectrum data.
However, the road spectrum data in the existing scheme does not include the vehicle load and the gradient, so that various performances of the vehicle cannot be accurately evaluated according to the road spectrum data. In the prior art, an acceleration sensor and a gradient sensor are often used for acquiring acceleration and gradient when gradient and vehicle load are calculated, so that a vehicle is required to be provided with various sensors, and additional cost is increased.
Disclosure of Invention
The invention provides a method, a device, equipment, a medium and a product for determining road spectrum data of a vehicle, which aim to solve the problem that the final road spectrum data can only be obtained by mounting various sensors on the vehicle in the prior art.
According to an aspect of the present invention, there is provided a road spectrum data determination method of a vehicle, including:
acquiring road spectrum data of a vehicle, and determining wheel driving force of the vehicle based on the road spectrum data, wherein the wheel driving force is positively correlated with a vehicle gear;
segmenting a road spectrum of a vehicle to obtain a plurality of road spectrum segments;
optimizing a resistance coefficient and a vehicle load in a vehicle dynamics formula corresponding to each road spectrum segment based on the wheel edge driving force, and determining a real vehicle load and a real road gradient in each road spectrum segment according to the optimized vehicle dynamics formula corresponding to each road spectrum segment;
and adding the real vehicle load and the real road gradient in each road spectrum segment into the road spectrum data to obtain the final road spectrum data of the vehicle.
According to another aspect of the present invention, there is provided a road spectrum data determination apparatus of a vehicle, including:
the road spectrum data acquisition module is used for acquiring road spectrum data of a vehicle and determining wheel driving force of the vehicle based on the road spectrum data, wherein the wheel driving force is positively correlated with a vehicle gear;
the segmentation module is used for segmenting a road spectrum of a vehicle to obtain a plurality of road spectrum segments;
The determining module is used for optimizing a resistance coefficient and a vehicle load in a vehicle dynamics formula corresponding to each road spectrum segment based on the wheel-side driving force, and determining a real vehicle load and a real road gradient in each road spectrum segment according to the optimized vehicle dynamics formula corresponding to each road spectrum segment;
and the adding module is used for adding the real vehicle load and the real road gradient in each road spectrum segment into the road spectrum data to obtain the final road spectrum data of the vehicle.
According to another aspect of the present invention, there is provided an electronic apparatus including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores a computer program executable by the at least one processor, the computer program being executable by the at least one processor to enable the at least one processor to perform a method of determining road spectrum data of a vehicle according to any embodiment of the present invention.
According to another aspect of the present invention, there is provided a computer-readable storage medium storing computer instructions for causing a processor to implement a method for determining road spectrum data of a vehicle according to any one of the embodiments of the present invention when the computer instructions are executed.
According to the technical scheme of the embodiment of the invention, the real vehicle load and the real road gradient are calculated through the road spectrum data of the vehicle to obtain the final road spectrum data, so that the problem that the road spectrum data in the prior art does not comprise the vehicle load and the road gradient is solved, and the beneficial effect of determining the real vehicle load and the real road gradient under the condition that an additional sensor is not required to be installed is achieved.
It should be understood that the statements in this section are not intended to identify key or critical features of the embodiments of the present invention, nor are they intended to limit the scope of the invention. Other features of the present invention will become apparent from the following description.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flowchart of a method for determining road spectrum data of a vehicle according to an embodiment of the present invention;
Fig. 2 is a schematic flowchart of a method for determining road spectrum data of a vehicle according to a second embodiment of the present invention;
FIG. 3 is a flowchart illustrating an exemplary method of determining road spectrum data for a vehicle according to the present invention;
FIG. 4 is a schematic diagram of a windage coefficient optimization provided by an exemplary embodiment of the present invention;
FIG. 5 is a schematic diagram of the optimization of the rolling resistance coefficient provided by an exemplary embodiment of the present invention;
fig. 6 is a schematic structural diagram of a road spectrum data determination device of a vehicle according to a third embodiment of the present invention;
fig. 7 is a schematic structural diagram of an electronic device of a method for determining road spectrum data of a vehicle according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, 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 making any creative effort, shall fall within the protection scope of the present invention. It should be understood that the various steps recited in the method embodiments of the present invention may be performed in a different order and/or performed in parallel. Moreover, method embodiments may include additional steps and/or omit performing the illustrated steps. The scope of the invention is not limited in this respect.
The term "including" and variations thereof as used herein is intended to be open-ended, i.e., "including but not limited to". The term "based on" is "based, at least in part, on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". Relevant definitions for other terms will be given in the following description.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It is noted that references to "a", "an", and "the" modifications in the present invention are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that reference to "one or more" unless the context clearly dictates otherwise.
The names of messages or information exchanged between devices in the embodiments of the present invention are for illustrative purposes only, and are not intended to limit the scope of the messages or information.
Example one
Fig. 1 is a flowchart of a method for determining road spectrum data of a vehicle according to an embodiment of the present invention, where the method is applicable to a case where vehicle performance is analyzed based on the road spectrum data, and the method may be executed by a road spectrum data determining apparatus of the vehicle, where the apparatus may be implemented by software and/or hardware and is generally integrated on an electronic device, where the electronic device includes, but is not limited to: a vehicle networking device.
As shown in fig. 1, a method for determining road spectrum data of a vehicle according to a first embodiment of the present invention includes the following steps:
s110, road spectrum data of the vehicle are obtained, and wheel driving force of the vehicle is determined based on the road spectrum data, wherein the wheel driving force is positively correlated with a vehicle gear.
In this embodiment, the road spectrum data of the vehicle may be collected by the road spectrum collecting device in the internet of vehicles, and one feasible way is to collect the road spectrum data by a T-box installed on the vehicle, the engine broadcasts the final information in the CAN bus according to the SAEJ1939 protocol, and the T-box collects, records and returns the road spectrum data to the back-end internet of vehicles database.
The road spectrum data can be understood as original road spectrum data, and the road spectrum data can comprise engine speed, output torque, oil consumption, vehicle speed, clutch state, brake state and atmospheric pressure.
In this embodiment, it may be determined whether the clutch state is a semi-interlocking state or an non-interlocking state first from the clutch signal recorded in the road spectrum data, and if the clutch state is a semi-interlocking state or a non-interlocking state, the wheel-side driving force of the vehicle may be determined based on the engine speed and the vehicle speed in the road spectrum data.
Specifically, the determining the wheel-side driving force of the vehicle based on the initial road spectrum data includes: when the clutch state of the vehicle is a semi-linkage state or a non-linkage state, determining the speed ratio of the rotating speed vehicle at different moments according to the speed and the engine speed at different moments in the initial road spectrum data, wherein the clutch state is determined according to a clutch signal in the initial road spectrum data; performing cluster identification on the speed ratio of the rotating speed vehicle to obtain the total transmission ratio of a transmission system; and obtaining the wheel driving force of the vehicle according to the product of a preset coefficient, the total transmission ratio of the transmission system and the output torque of the engine, wherein the product of the preset coefficient and the total transmission ratio of the transmission system is positively correlated with the gear.
The rotating speed-vehicle speed ratio can be a ratio of a vehicle speed to a rotating speed, and the rotating speed-vehicle speed ratio can also be understood as a transmission ratio of engine torque to wheel-side driving force. The speed ratio of the rotating speed is gathered near a plurality of data points, the number of gathering centers is the same as the number of gears of the gearbox, and the total transmission ratio of the transmission system can be calculated according to the variation trend of the speed ratio of the rotating speed and a related clustering algorithm.
The wheel edge driving force calculation formula is as follows: f ═ T × N/V × 0.377. F may represent the wheel-side driving force in units of N; t may represent the output torque of the engine in Nm; n may represent engine speed in units of l/min; v may represent vehicle speed in km/h.
In this embodiment, since N/V0.377 is a fixed value related to the shift position, the wheel-side driving force may be calculated by the following formula: F-T N/V0.377-T inNamely, gear identification can be carried out according to the rotating speed and the vehicle speed ratio, and the corresponding part is replaced by inN represents a shift position, and i represents a rotational speed ratio corresponding to each shift position.
In the embodiment, since the rear axle speed ratio and the tire model are generally fixed, the rear axle speed ratio and the tire model can be roughly judged and determined according to the vehicle speed, the vehicle load, the running area of the vehicle and the like, and therefore the gear speed ratio of each gearbox can be obtained.
And S120, segmenting the road spectrum of the vehicle to obtain a plurality of road spectrum segments.
In the present embodiment, due to the continuity of data in a single road spectrum segment, it can be considered that the vehicle load and the vehicle resistance coefficient are kept unchanged in the single road spectrum segment, so that the parameters in the vehicle dynamics formula can be optimized in the single road spectrum segment. The road spectrum segmentation can be performed according to the vehicle speed in the road spectrum data.
Specifically, the segmenting the road spectrum of the vehicle to obtain a plurality of road spectrum segments includes: segmenting the driving distance of the vehicle according to the vehicle speed in the initial road spectrum data to obtain a plurality of short strokes; and dividing the short strokes of which the interval time is less than the preset time length in the plurality of short strokes into a road spectrum segment.
The short journey comprises a corresponding driving distance in the process that the vehicle speed of the vehicle is changed into an initial value after being accelerated from the initial value. For example, the initial value may be 0, and short strokes with an interval time shorter than 5 minutes may be regarded as continuous data and divided into one road spectrum segment.
S130, optimizing the coefficient and the vehicle load in the vehicle dynamics formula corresponding to each road spectrum segment based on the wheel-side driving force, and determining the real vehicle load and the real road gradient in each road spectrum segment according to the optimized vehicle dynamics formula corresponding to each road spectrum segment.
In the embodiment, the vehicle dynamics formula is a formula for calculating the wheel-side driving force, since the wheel-side driving force is a known value, in a single road spectrum segment, the road gradient can be reversely deduced according to the wheel-side driving force formula, and the longitudinal speed integral calculated according to the road gradient and the vehicle speed is the elevation; calculating a real altitude according to the atmospheric pressure value, comparing the altitudes calculated by the two modes, and optimizing the wind resistance coefficient, the rolling resistance coefficient and the vehicle load in the vehicle dynamics formula by using the minimum square sum of the errors of the two modes as the final optimization to obtain a real vehicle load; and reversely deducing the true road gradient according to the optimized vehicle dynamics formula.
Specifically, optimizing a coefficient and a vehicle load in a vehicle dynamics formula corresponding to each road spectrum segment based on the wheel-side driving force, and determining a real vehicle load and a real road gradient in each road spectrum segment according to the optimized vehicle dynamics formula corresponding to each road spectrum segment, includes: for a single road spectrum segment, determining a road gradient based on the wheel driving force and a vehicle dynamic formula corresponding to the single road spectrum segment; integrating the longitudinal component of the product of the road gradient and the vehicle speed in the single road spectrum segment to obtain the accumulated altitude of the gradient, wherein the vehicle speed in the single road spectrum segment is obtained from the initial road spectrum data; determining the true altitude of the slope according to the atmospheric pressure in the initial road spectrum data; optimizing the wind resistance coefficient, the rolling resistance coefficient and the vehicle load in the vehicle dynamic formula corresponding to the single road spectrum segment by taking the minimum value of the sum of squares of the actual altitude and the accumulated altitude difference as an optimization target to obtain the actual vehicle load in the single road spectrum segment; and calculating the real road gradient in the single road spectrum segment according to the optimized dynamic formula.
In this embodiment, the vehicle dynamics formula is:
wherein F represents a wheel rim driving force in a unit of N; a represents the frontal area of the vehicle in m2(ii) a CA represents a wind resistance coefficient; v represents vehicle speed in m/s; g represents the acceleration of gravity in m/s2(ii) a θ represents the gradient; fr represents the rolling resistance coefficient; m represents vehicle load in kg; a represents the acceleration of the vehicle in m/s2。
The determination mode of the acceleration in the vehicle dynamics formula corresponding to the single road spectrum segment is as follows: and determining acceleration according to the vehicle speed in the single road spectrum segment, filtering the acceleration, and performing data alignment on the filtered acceleration and the engine output torque in the initial road spectrum data to obtain the vehicle acceleration.
Wherein the longitudinal component of the product of road grade and vehicle speed within a single road spectrum segment may be denoted as V × cos (θ); the calculation formula for the sum of the squares of the errors between the accumulated altitude and the true altitude is:
in this embodiment, the wind resistance coefficient, the roll resistance coefficient and the vehicle load can be optimized one by one through the above method, the obtained optimal vehicle load is the real vehicle load, the optimized vehicle dynamics formula can be obtained according to the optimized wind resistance coefficient, the optimized roll resistance coefficient and the vehicle load, the road gradient can be reversely deduced according to the optimized vehicle dynamics formula, and the road gradient is optimized through a least square method to obtain the real road gradient.
It should be noted that, whether the vehicle is in a braking state is determined according to braking data in the road spectrum data, and if the vehicle is in a non-braking state, the true gradient of the previous road spectrum segment is used as the true gradient of the current moment; if the vehicle is not in a braking state, the real road gradient can be calculated in the above mode.
And S140, adding the real vehicle load and the real road gradient in each road spectrum segment into the road spectrum data to obtain the final road spectrum data of the vehicle.
In this embodiment, for each road spectrum segment, the true vehicle load and the true road gradient in each road spectrum segment may be obtained through S130, the calculated multiple vehicle true loads and the true road gradients are added to the original road spectrum data, and road spectrum data including the vehicle true loads and the true road gradients may be obtained as final road spectrum data.
The method for determining the road spectrum data of the vehicle comprises the steps of firstly obtaining the road spectrum data of the vehicle, and determining the wheel driving force of the vehicle based on the road spectrum data; then segmenting the road spectrum of the vehicle to obtain a plurality of road spectrum segments; optimizing a resistance coefficient and a vehicle load in a vehicle dynamics formula corresponding to each road spectrum segment based on the wheel-side driving force, and determining a real vehicle load and a real road gradient in each road spectrum segment according to the optimized vehicle dynamics formula corresponding to each road spectrum segment; and finally adding the real vehicle load and the real road gradient in each road spectrum segment into the road spectrum data to obtain the final road spectrum data of the vehicle. With the above method, road spectrum data including the true vehicle load and the true road gradient can be obtained without increasing the additional cost of the vehicle.
Example two
Fig. 2 is a schematic flow chart of a method for determining road spectrum data of a vehicle according to a second embodiment of the present invention, and the second embodiment is optimized based on the above embodiments. In this embodiment, after obtaining the final road spectrum data of the vehicle, the method further includes: analyzing the dynamic property and the economical property of the vehicle based on the final road spectrum data; and extracting a typical road spectrum based on the final road spectrum data. Please refer to the first embodiment for a detailed description of the present embodiment.
As shown in fig. 2, a second embodiment of the present invention provides a method for determining road spectrum data of a vehicle, including the following steps:
s210, road spectrum data of the vehicle are obtained, and wheel driving force of the vehicle is determined based on the road spectrum data, wherein the wheel driving force is positively correlated with a vehicle gear.
S220, segmenting the road spectrum of the vehicle to obtain a plurality of road spectrum segments.
And S230, optimizing the coefficient and the vehicle load in the vehicle dynamics formula corresponding to each road spectrum segment based on the wheel edge driving force, and determining the real vehicle load and the real road gradient in each road spectrum segment according to the optimized vehicle dynamics formula corresponding to each road spectrum segment.
And S240, adding the real vehicle load and the real road gradient in each road spectrum segment into the road spectrum data to obtain the final road spectrum data of the vehicle.
And S250, analyzing the dynamic property and the economical efficiency of the vehicle based on the final road spectrum data.
In the present embodiment, the isovelocity segment that can be used for evaluating the vehicle dynamics, and the acceleration segment that can be used for evaluating the vehicle economy can be extracted from the road spectrum according to the vehicle speed in the final road spectrum data. The dynamic performance of different vehicles of the same model can be compared by comparing the acceleration of different vehicles with the same vehicle load, the same real road gradient, the same accelerator and the same model in an acceleration segment; the economic performance of different vehicles of the same type can be compared by comparing the acceleration of different vehicles of the same type in a constant speed segment with corresponding vehicle load, the same real road gradient, the same speed and the same type.
Specifically, the analysis of the dynamic property of the vehicle based on the final road spectrum data includes: determining an acceleration driving segment according to the final road spectrum data; obtaining a plurality of second real vehicle loads, a plurality of second real road gradients and throttle values within the acceleration driving section from the final road spectrum data; determining a final acceleration driving segment having the same second real vehicle load, the same second real road grade, and the same throttle value; and analyzing the dynamic property of the vehicle according to the average acceleration in the final uniform speed running segment.
Illustratively, the accelerated running segments of which the vehicle load is full, the real gradient of the road is less than 2 degrees and the accelerator is more than 90 percent are extracted from the final road spectrum, the vehicle speed is 0-20km/h, 20km/h-40km/h and 40km/h-60km/h, the average acceleration in the accelerated running segments is calculated, and the dynamic property of each vehicle can be judged by comparing the average acceleration of different vehicles of the same vehicle type in the accelerated running segments. Wherein the larger the average acceleration, the better the dynamic property of the vehicle is represented.
Specifically, the analysis of the vehicle economy based on the final road spectrum data includes: determining a constant-speed driving segment according to the final road spectrum data; obtaining a plurality of first real vehicle loads and a plurality of first real road gradients within the uniform speed driving segment from the final road spectrum data; determining a final constant speed driving segment with the same first real vehicle load and the same first real road gradient; and analyzing the economy of the vehicle according to the acceleration in the final uniform speed driving segment.
Illustratively, segments with full vehicle load, real road gradient less than 2 degrees and vehicle speed of 40km/h +/-2 km/h, 50km/h +/-2 km/h, 60km/h +/-2 km/h, 70km/h +/-2 km/h and duration of more than 1 minute are extracted from the final road spectrum data, namely final constant-speed driving segments, the average oil consumption in the segments is calculated, and the economical condition of the segments can be judged by comparing the average oil consumption with the earlier road spectrum data of the vehicle and other vehicle results.
It should be noted that, the acceleration traveling segments and the constant speed traveling segments extracted from the road spectrum are classified according to the actual vehicle load and the actual road gradient in the final road spectrum data, so that the influence of the vehicle load and the road gradient on the acceleration performance and the economy of the vehicle can be avoided, and the comparison result of the acceleration performance and the economy of the vehicle is more accurate.
And S260, extracting a typical road spectrum based on the final road spectrum data.
In the embodiment, feature segment extraction is carried out on the road spectrum according to feature values calculated by real vehicle load, real road gradient, vehicle speed, engine speed and output torque in final road spectrum data, segments are divided according to short travel, a short typical road spectrum is generated by adopting a fuzzy clustering algorithm, and the road spectrum can intuitively embody the features of a complete road spectrum and the distribution characteristics of working conditions.
Specifically, the extracting a typical road spectrum based on the final road spectrum data includes: dividing the final road spectrum data into a plurality of road spectrum fragments; calculating characteristic values of a plurality of road spectrum fragments based on the final road spectrum data; dividing the road spectrum fragments into a preset number of categories through principal component analysis and fuzzy clustering according to the characteristic values; determining an average characteristic value of the road spectrum fragments of each category, and determining at least one typical road spectrum fragment from the road spectrum fragments of each category according to the average characteristic value; and combining the determined typical road spectrum fragments to obtain a typical road spectrum.
For example, for a single road spectrum segment, the average vehicle speed, the vehicle speed interval, the average rotation speed, the rotation speed interval, the average torque, the gear, the true road gradient, the true vehicle load, and the like within the single road spectrum segment are calculated as the characteristic values of the single road spectrum segment. The characteristic values of all road spectrum segments can be obtained according to the method. And considering that the road spectrum segments with similar characteristic values are similar, clustering, dividing all the road spectrum segments into 3-5 classes according to the characteristic values by using principal component analysis and fuzzy clustering, extracting one or more representative road spectrum segments in each class according to the average characteristic value of each class, enabling the characteristic value of the extracted representative road spectrum segment to be close to the average characteristic value of the road spectrum segment, and recombining the extracted representative road spectrum segment into a new road spectrum according to the time ratio of the road spectrum segments, namely the representative road spectrum.
The extracted typical road spectrum has the same working condition distribution as the original road spectrum data and can represent the running road spectrum of the vehicle in a period of time. Through the extracted typical road spectrum, the use scene of the user can be described, and an important basis is provided for product development and scene market application.
The method for determining the road spectrum data of the vehicle provided by the embodiment of the invention embodies the processes of analyzing the economy and the dynamic property of the vehicle based on the final road spectrum data and extracting a typical road spectrum. By using the method, the road spectrum data can be widely applied to the dynamic and economic evaluation of vehicles and the typical road spectrum extraction, the utilization rate of the road spectrum data is improved, the value of large data is fully mined, and important basis is provided for product research and development and market service.
The embodiments of the present invention provide several specific implementation manners based on the technical solutions of the above embodiments.
Fig. 3 is a flowchart illustrating an example of a method for determining road spectrum data of a vehicle according to the present invention, as shown in fig. 3, including the following steps:
The original road spectrum data comprise the rotating speed, the torque, the oil consumption, the vehicle speed, a clutch signal, a brake state, the atmospheric pressure and the like of the engine.
And 2, screening and filtering effective data.
Calculating the speed ratio of the rotating speed vehicle according to the rotating speed of the engine, the vehicle speed and the clutch signal, and finishing gear identification; calculating the acceleration of the vehicle through the vehicle speed difference, performing low-pass filtering on the acceleration, and performing data alignment on the acceleration according to the torque; and calculating the wheel driving force according to the output torque of the engine and the rotating speed vehicle speed ratio.
And 3, dividing the road spectrum.
The road spectrum is divided into a plurality of road spectrum segments according to the speed of the vehicle, one road spectrum segment corresponds to one short stroke, and the weight of the vehicle, namely the load and the resistance coefficient of the vehicle in a single road spectrum segment are kept unchanged.
And 4, calculating the vehicle weight, the resistance coefficient and the road gradient corresponding to each road spectrum segment.
The step is corresponding to the first embodiment, the resistance coefficient and the vehicle load in the vehicle dynamics formula corresponding to each road spectrum segment are optimized based on the wheel-side driving force, and the real vehicle load and the real road gradient in each road spectrum segment are determined according to the optimized vehicle dynamics formula corresponding to each road spectrum segment.
The process of optimizing the vehicle resistance coefficient and the vehicle weight can be embodied as follows: calculating the gradient of the processed road spectrum data, the resistance and the vehicle weight through a dynamic formula to obtain the square sum of the gradient calculation altitude and the atmospheric pressure altitude error; judging whether the optimization cycle number meets a set value; if not, adjusting the vehicle weight and the resistance coefficient, and then returning to the step of calculating the gradient according to a dynamic formula; if yes, the vehicle weight and the resistance coefficient with the minimum error are output. Wherein the drag coefficient comprises a wind drag coefficient and a rolling drag coefficient.
Fig. 4 is a schematic diagram of optimization of a wind resistance coefficient according to an exemplary embodiment of the present invention, and as shown in fig. 4, an abscissa represents the wind resistance coefficient, an ordinate represents a sum of squares of errors between a gradient calculation altitude and an atmospheric pressure altitude, and a corresponding wind resistance coefficient when the sum of squares of errors reaches a minimum value is the optimized wind resistance coefficient.
Fig. 5 is a schematic diagram illustrating optimization of a rolling resistance coefficient according to an exemplary embodiment of the present invention, where as shown in fig. 5, an abscissa represents the rolling resistance coefficient, an ordinate represents a sum of squares of errors between a gradient calculation altitude and an atmospheric pressure altitude, and a corresponding rolling resistance coefficient when the sum of squares of errors reaches a minimum value is an optimized rolling resistance coefficient.
Wherein the process of calculating the gradient through the dynamic formula may include: judging whether the clutch is disengaged or the brake is stepped on, if so, keeping the gradient unchanged; if not, acquiring processed road spectrum data, the vehicle weight and the resistance coefficient when the error is minimum, and calculating the speed ratio of the rotating speed vehicle and the wheel driving force; and calculating the gradient according to a dynamic formula, and optimizing the gradient by a least square method to obtain the true road gradient.
And 5, determining whether all road spectrum segments are completely calculated.
If yes, executing step 6; if not, returning to execute the step 4.
And 6, integrating and outputting the real gradient and the real vehicle weight to obtain final road spectrum data.
And 7, analyzing the dynamic property and the economic property of the vehicle and extracting a typical road spectrum.
In this step, the dynamic property analysis may include the following processes: extracting an acceleration segment according to the final road spectrum data; classifying the acceleration segments according to the speed interval, the real vehicle weight and the real gradient; calculating a segment acceleration section, and comparing the dynamic properties of similar segments; and (4) comprehensively analyzing the dynamic property of each acceleration segment, and exporting the dynamic property data to a dynamic property database.
In this step, the economic analysis may include the following processes: extracting uniform-speed segments according to the final road spectrum data; classifying the uniform speed segments according to the speed, the real weight and the real gradient; calculating the average oil consumption in different classification segments, comparing the economy of the same type of segments, comprehensively analyzing the economy of each uniform-speed segment to obtain economy data, and importing the obtained economy data into an economy database.
In this step, a typical road spectrum extraction may include the following processes: dividing the road spectrum into a plurality of road spectrum segments according to the final road spectrum data, and extracting characteristic values of the single road spectrum segment; finishing road spectrum segment clustering and road spectrum segment recombination according to the characteristic values to obtain a typical road spectrum; judging whether the typical road spectrum working condition distribution is qualified, if so, outputting the typical road spectrum; if not, the step of completing road spectrum segment clustering and road spectrum segment recombination according to the characteristic values is returned after the characteristic values and the clustering algorithm are optimized.
EXAMPLE III
Fig. 6 is a schematic structural diagram of a road spectrum data determining apparatus for a vehicle according to a third embodiment of the present invention, which is applicable to a situation where vehicle performance is analyzed based on road spectrum data, where the apparatus may be implemented by software and/or hardware and is generally integrated on an electronic device.
As shown in fig. 6, the apparatus includes: an acquisition module 110, a segmentation module 120, a determination module 130, and an addition module 140.
An obtaining module 110, configured to obtain road spectrum data of a vehicle, and determine a wheel-side driving force of the vehicle based on the road spectrum data, where the wheel-side driving force is positively correlated with a vehicle gear;
a segmentation module 120, configured to segment a road spectrum of a vehicle to obtain a plurality of road spectrum segments;
the determining module 130 is configured to optimize a resistance coefficient and a vehicle load in a vehicle dynamics formula corresponding to each road spectrum segment based on the wheel-side driving force, and determine a real vehicle load and a real road gradient in each road spectrum segment according to the optimized vehicle dynamics formula corresponding to each road spectrum segment;
and an adding module 140, configured to add the actual vehicle load and the actual road gradient in each road spectrum segment to the road spectrum data to obtain final road spectrum data of the vehicle.
In the embodiment, the apparatus first obtains road spectrum data of the vehicle through the obtaining module 110, and determines wheel-side driving force of the vehicle based on the road spectrum data, wherein the wheel-side driving force is positively correlated with a vehicle gear; then, the road spectrum of the vehicle is segmented by a segmentation module 120 to obtain a plurality of road spectrum segments; then, optimizing the resistance coefficient and the vehicle load in the vehicle dynamics formula corresponding to each road spectrum segment by the determining module 130 based on the wheel-side driving force, and determining the real vehicle load and the real road gradient in each road spectrum segment according to the optimized vehicle dynamics formula corresponding to each road spectrum segment; and finally, adding the real vehicle load and the real road gradient in each road spectrum segment into the road spectrum data through an adding module 140 to obtain the final road spectrum data of the vehicle.
The present embodiment provides a road spectrum data determination device for a vehicle, which is capable of obtaining road spectrum data including a true vehicle load and a true road gradient without increasing additional cost of the vehicle.
Further, the obtaining module 110 is specifically configured to: when the clutch state of the vehicle is a semi-linkage state or a non-linkage state, determining the speed ratio of the rotating speed vehicle at different moments according to the speed and the engine speed at different moments in the initial road spectrum data, wherein the clutch state is determined according to a clutch signal in the initial road spectrum data; performing cluster identification on the speed ratio of the rotating speed vehicle to obtain the total transmission ratio of a transmission system; and obtaining the wheel driving force of the vehicle according to a product of a preset coefficient, the total transmission ratio of the transmission system and the output torque of the engine, wherein the product of the preset coefficient and the total transmission ratio of the transmission system is positively correlated with the gear.
On the basis of the above optimization, the segmentation module 120 is specifically configured to: segmenting the driving distance of the vehicle according to the vehicle speed in the initial road spectrum data to obtain a plurality of short strokes; dividing short strokes with the interval time smaller than the preset time length in the short strokes into a road spectrum segment; wherein, a short journey comprises a corresponding driving distance in the process that the vehicle speed of the vehicle is changed into the initial value after being accelerated from the initial value.
Based on the above technical solution, the determining module 130 is specifically configured to: for a single road spectrum segment, determining a road gradient based on the wheel driving force and a vehicle dynamic formula corresponding to the single road spectrum segment; integrating the longitudinal component of the product of the road gradient and the vehicle speed in the single road spectrum segment to obtain the accumulated altitude of the gradient, wherein the vehicle speed in the single road spectrum segment is obtained from the initial road spectrum data; determining the true altitude of the slope according to the atmospheric pressure in the initial road spectrum data; optimizing the wind resistance coefficient, the rolling resistance coefficient and the vehicle load in the vehicle dynamic formula corresponding to the single road spectrum segment by taking the minimum value of the sum of squares of the actual altitude and the accumulated altitude difference as an optimization target to obtain the actual vehicle load in the single road spectrum segment; calculating the real road gradient in the single road spectrum segment according to the optimized dynamic formula;
The determination mode of the acceleration in the vehicle dynamics formula corresponding to the single road spectrum segment is as follows: and determining an acceleration according to the vehicle speed in the single road spectrum segment, filtering the acceleration, and performing data alignment on the filtered acceleration and the engine output torque in the initial road spectrum data to obtain the vehicle acceleration.
Further, the device also comprises an analysis module and an extraction module.
The analysis module is specifically configured to: analyzing the dynamic property and the economical property of the vehicle based on the final road spectrum data; the extraction module is specifically configured to: and extracting a typical road spectrum based on the final road spectrum data.
The analysis module comprises a first analysis module and a second analysis module.
Specifically, the first analysis module is specifically configured to: determining a constant-speed driving segment according to the final road spectrum data; obtaining a plurality of first real vehicle loads and a plurality of first real road gradients in the constant speed driving segment from the final road spectrum data; determining a final constant speed driving segment with the same first real vehicle load and the same first real road gradient; and analyzing the economy of the vehicle according to the acceleration in the final uniform speed running segment.
Specifically, the second analysis module is specifically configured to: determining an acceleration driving segment according to the final road spectrum data; obtaining a plurality of second real vehicle loads, a plurality of second real road gradients and throttle values within the acceleration driving section from the final road spectrum data; determining a final acceleration driving segment having the same second real vehicle load, the same second real road gradient and the same throttle value; and analyzing the dynamic property of the vehicle according to the average acceleration in the final uniform speed running section.
Further, the extraction module is specifically configured to: dividing the final road spectrum data into a plurality of road spectrum fragments; calculating characteristic values of a plurality of road spectrum fragments based on the final road spectrum data; dividing the road spectrum fragments into a preset number of categories through principal component analysis and fuzzy clustering according to the characteristic values; determining an average characteristic value of the road spectrum fragments of each category, and determining at least one typical road spectrum fragment from the road spectrum fragments of each category according to the average characteristic value; and combining the determined typical road spectrum fragments to obtain a typical road spectrum.
The road spectrum data determining device of the vehicle can execute the road spectrum data determining method of the vehicle provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the executing method.
Example four
FIG. 7 illustrates a block diagram of an electronic device 10 that may be used to implement an embodiment of the invention. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the inventions described and/or claimed herein.
As shown in fig. 7, the electronic device 10 includes at least one processor 11, and a memory communicatively connected to the at least one processor 11, such as a Read Only Memory (ROM)12, a Random Access Memory (RAM)13, and the like, wherein the memory stores a computer program executable by the at least one processor, and the processor 11 can perform various suitable actions and processes according to the computer program stored in the Read Only Memory (ROM)12 or the computer program loaded from a storage unit 18 into the Random Access Memory (RAM) 13. In the RAM 13, various programs and data necessary for the operation of the electronic apparatus 10 may also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other via a bus 14. An input/output (I/O) interface 15 is also connected to the bus 14.
A number of components in the electronic device 10 are connected to the I/O interface 15, including: an input unit 16 such as a keyboard, a mouse, or the like; an output unit 17 such as various types of displays, speakers, and the like; a storage unit 18 such as a magnetic disk, optical disk, or the like; and a communication unit 19 such as a network card, modem, wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The processor 11 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various processors running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, or the like. The processor 11 performs the various methods and processes described above, such as a method of determining road spectrum data for a vehicle.
In some embodiments, the method of determining road spectrum data for a vehicle may be implemented as a computer program tangibly embodied in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 10 via the ROM 12 and/or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the method of determining road spectrum data of a vehicle described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured by any other suitable means (e.g., by means of firmware) to perform the road spectrum data determination method of the vehicle.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
A computer program for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions/acts specified in the flowchart and/or block diagram block or blocks to be performed. A computer program can execute entirely on a machine, partly on a machine, as a stand-alone software package partly on a machine and partly on a remote machine or entirely on a remote machine or server.
In the context of the present invention, a computer-readable storage medium may be a tangible medium that can contain, or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. Alternatively, the computer readable storage medium may be a machine readable signal medium. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the electronic device. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), blockchain networks, and the internet.
The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service are overcome.
It should be understood that various forms of the flows shown above, reordering, adding or deleting steps, may be used. For example, the steps described in the present invention may be executed in parallel, sequentially, or in different orders, and are not limited herein as long as the desired results of the technical solution of the present invention can be achieved.
The above-described embodiments should not be construed as limiting the scope of the invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (12)
1. A method of determining road spectrum data for a vehicle, the method comprising:
acquiring road spectrum data of a vehicle, and determining wheel driving force of the vehicle based on the road spectrum data, wherein the wheel driving force is positively correlated with a vehicle gear;
segmenting a road spectrum of a vehicle to obtain a plurality of road spectrum segments;
optimizing a resistance coefficient and a vehicle load in a vehicle dynamics formula corresponding to each road spectrum segment based on the wheel-side driving force, and determining a real vehicle load and a real road gradient in each road spectrum segment according to the optimized vehicle dynamics formula corresponding to each road spectrum segment;
And adding the real vehicle load and the real road gradient in each road spectrum segment into the road spectrum data to obtain the final road spectrum data of the vehicle.
2. The method of claim 1, wherein determining a wheel-side driving force of a vehicle based on the initial road spectrum data comprises:
when the clutch state of the vehicle is a semi-linkage state or a non-linkage state, determining the speed ratio of the rotating speed vehicle at different moments according to the speed and the rotating speed of the engine at different moments in the initial road spectrum data, wherein the clutch state is determined according to a clutch signal in the initial road spectrum data;
performing cluster identification on the speed ratio of the rotating speed vehicle to obtain the total transmission ratio of a transmission system;
and obtaining the wheel driving force of the vehicle according to the product of a preset coefficient, the total transmission ratio of the transmission system and the output torque of the engine, wherein the product of the preset coefficient and the total transmission ratio of the transmission system is positively correlated with the gear.
3. The method of claim 1, wherein segmenting the road spectrum of the vehicle into a plurality of road spectrum segments comprises:
segmenting the driving distance of the vehicle according to the vehicle speed in the initial road spectrum data to obtain a plurality of short strokes;
Dividing short strokes with the interval time smaller than a preset time length in the plurality of short strokes into a road spectrum segment;
the short journey comprises a corresponding driving distance in the process that the vehicle speed of the vehicle is changed into an initial value after being accelerated from the initial value.
4. The method of claim 1, wherein optimizing the drag coefficient and vehicle load in the vehicle dynamics formula for each road spectrum segment based on the wheel-side driving force, determining a true vehicle load and a true road grade within each road spectrum segment from the optimized vehicle dynamics formula for each road spectrum segment, comprises:
for a single road spectrum segment, determining a road gradient based on the wheel driving force and a vehicle dynamic formula corresponding to the single road spectrum segment;
integrating the longitudinal component of the product of the road gradient and the vehicle speed in the single road spectrum segment to obtain the accumulated altitude of the gradient, wherein the vehicle speed in the single road spectrum segment is obtained from the initial road spectrum data;
determining the true altitude of the slope according to the atmospheric pressure in the initial road spectrum data;
optimizing the wind resistance coefficient, the rolling resistance coefficient and the vehicle load in the vehicle dynamic formula corresponding to the single road spectrum segment by taking the minimum value of the sum of squares of the actual altitude and the accumulated altitude difference as an optimization target to obtain the actual vehicle load in the single road spectrum segment;
Calculating the real road gradient in the single road spectrum segment according to the optimized dynamic formula;
the determination mode of the acceleration in the vehicle dynamics formula corresponding to the single road spectrum segment is as follows: and determining acceleration according to the vehicle speed in the single road spectrum segment, filtering the acceleration, and performing data alignment on the filtered acceleration and the engine output torque in the initial road spectrum data to obtain the vehicle acceleration.
5. The method of claim 1, after obtaining the final road spectrum data for the vehicle, further comprising:
analyzing the dynamic property and the economical property of the vehicle based on the final road spectrum data;
and extracting a typical road spectrum based on the final road spectrum data.
6. The method of claim 5, wherein analyzing the vehicle's economy based on the final road spectrum data comprises:
determining a constant-speed driving segment according to the final road spectrum data;
obtaining a plurality of first real vehicle loads and a plurality of first real road gradients in the constant speed driving segment from the final road spectrum data;
determining a final constant speed driving segment with the same first real vehicle load and the same first real road gradient;
And analyzing the economy of the vehicle according to the acceleration in the final uniform speed driving segment.
7. The method of claim 5, wherein analyzing the dynamics of the vehicle based on the final road spectrum data comprises:
determining an acceleration driving segment according to the final road spectrum data;
obtaining a plurality of second real vehicle loads, a plurality of second real road gradients and throttle values within the acceleration driving section from the final road spectrum data;
determining a final acceleration driving segment having the same second real vehicle load, the same second real road grade, and the same throttle value;
and analyzing the dynamic property of the vehicle according to the average acceleration in the final uniform speed running segment.
8. The method of claim 5, wherein extracting a representative road spectrum based on the final road spectrum data comprises:
dividing the final road spectrum data into a plurality of road spectrum segments;
calculating characteristic values of a plurality of road spectrum fragments based on the final road spectrum data;
dividing the road spectrum fragments into a preset number of categories through principal component analysis and fuzzy clustering according to the characteristic values;
Determining an average characteristic value of the road spectrum fragments of each category, and determining at least one typical road spectrum fragment from the road spectrum fragments of each category according to the average characteristic value;
and combining the determined typical road spectrum fragments to obtain a typical road spectrum.
9. A road spectrum data determination apparatus of a vehicle, characterized by comprising:
the system comprises an acquisition module, a transmission module and a control module, wherein the acquisition module is used for acquiring road spectrum data of a vehicle and determining wheel driving force of the vehicle based on the road spectrum data, and the wheel driving force is positively correlated with a vehicle gear;
the segmentation module is used for segmenting a road spectrum of the vehicle to obtain a plurality of road spectrum segments;
the determining module is used for optimizing a resistance coefficient and a vehicle load in a vehicle dynamics formula corresponding to each road spectrum segment based on the wheel-side driving force, and determining a real vehicle load and a real road gradient in each road spectrum segment according to the optimized vehicle dynamics formula corresponding to each road spectrum segment;
and the adding module is used for adding the real vehicle load and the real road gradient in each road spectrum segment into the road spectrum data to obtain the final road spectrum data of the vehicle.
10. An electronic device, characterized in that the electronic device comprises:
At least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the first and the second end of the pipe are connected with each other,
the memory stores a computer program executable by the at least one processor to enable the at least one processor to perform the method of determining road spectrum data for a vehicle of any one of claims 1-8.
11. A computer-readable storage medium, characterized in that the computer-readable storage medium stores computer instructions for causing a processor to implement the method of determining road spectrum data of a vehicle of any one of claims 1-8 when executed.
12. A computer program product, characterized in that the computer program product comprises a computer program which, when being executed by a processor, carries out a method of road spectrum data determination of a vehicle according to any one of claims 1-8.
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