CN105651254B - Algorithm of road slope estimation based on road alignment and spectrum signature - Google Patents
Algorithm of road slope estimation based on road alignment and spectrum signature Download PDFInfo
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Abstract
The present invention relates to a kind of Algorithm of road slope estimation based on road alignment and spectrum signature, solve the problems, such as that operating condition design can not be applied to because strong to gps signal dependence existing for road grade information, error are big in existing vehicle operational mode design, comprise the following steps：1st, gathered data and raw data base Database is established；2nd, processing data：By the data frequency reducing in raw data base Database, the altitude value for setting the idling moment is unified value hidle, traveling section is divided into several micro travels, and micro travel distance is less than setting limit value sminMicro travel be merged into adjacent micro travel；3rd, gradient mileage i in micro travel is calculated3‑s3；4th, gradient time i is converted4‑t4Sequence：Gradient mileage i in the micro travel calculated to step S33‑s3Data merge, and by gradient mileage i overall after merging4‑s4Data according to vehicle mileage time s1‑t1Data are converted into gradient time i4‑t4Data output.
Description
Technical Field
The invention relates to a road gradient calculation method, in particular to a road gradient calculation method based on road alignment and frequency spectrum characteristics, which is applied to working condition design.
Background
Fuel consumption and emission of a vehicle are important indicators for evaluating the vehicle. When measuring the fuel consumption and the emission of a vehicle, the vehicle is usually operated on an indoor rotary drum test bed for a period of time according to a standard operation condition, and the emission of the vehicle during the period of time is measured. The standard working condition comprises speed and acceleration data of vehicle operation, and the road slope value is assumed to be a fixed value of zero. However, when the vehicle is operated with a change in the actual road gradient, the standard zero gradient may not reflect the actual situation, and it is not necessarily sufficient to accurately predict the fuel consumption and the emission of the vehicle.
Heavy vehicles and hybrid electric vehicles are very sensitive to road gradient changes, and different road gradients can obviously affect the running conditions of the vehicles, so that the accurate road gradient calculation method has great significance for the design of the running conditions of the vehicles. The most common methods for acquiring the road gradient information in the vehicle running process are two, wherein one method is to calculate the road gradient by using a state estimation method starting from a kinetic equation; the other is to calculate the road grade based on the GPS elevation information.
The method for estimating the state is used for calculating the gradient, information such as driving torque, vehicle speed and wind speed of an engine needs to be accurately measured, accurate measurement of the parameters has certain difficulty, and a calculated gradient value has certain error. The existing method for calculating the road slope value based on the GPS elevation information mainly uses the ratio delta h/delta s of the elevation difference acquired by the GPS and the horizontal displacement difference of the vehicle, and the ratio delta h/delta s is used as the calculated value of the road slope after simple filtering. Therefore, the existing method for calculating the road gradient value through the GPS information is a method for directly calculating the road gradient by using the GPS elevation information and the position information, because the method has strong dependence on GPS signals, when the GPS signals are interfered, the error of the calculation result of the road gradient is extremely large, the calculation result is seriously deviated from the true value, the result is directly applied to the design of the vehicle running condition and can influence the evaluation on the dynamic property and the economical property of the vehicle, the designed running condition of the aspect causes the insufficient or overlarge power output of the vehicle, and the aspect provides unreasonable power requirements for a controller, thereby increasing the fuel consumption. Ultimately resulting in inconsistent performance of the design vehicle dynamics and economics on both the test rig and the actual road.
Disclosure of Invention
The invention aims to solve the problem that the existing automobile operation condition design cannot be applied to the operation condition design due to strong dependence on GPS signals and large error of road gradient information, and provides a road gradient calculation method with high accuracy based on road alignment and spectral characteristics, which is used for designing more reasonable automobile operation conditions.
In order to achieve the purpose, the invention adopts the technical scheme that:
a road gradient calculation method based on road alignment and spectral features comprises the following steps:
s1: collecting data and establishing an original Database;
s2: processing data;
data in an original Database are subjected to frequency reduction, and the altitude value at the idle time (the vehicle running speed is less than 0.1m/s for two continuous seconds) is set as a uniform value h idle Dividing the driving section into a plurality of micro-strokes, and enabling the micro-stroke distance to be smaller than a set limit value s min Merging the micro-strokes into adjacent micro-strokes;
s3: calculating slope-mileage i in micro-stroke 3 -s 3 ；
Firstly, calculating a gradient value i with road mileage interval of 1 meter according to the data processed in the step S2 3 (ii) a Secondly, for the gradient value i 3 Performing power spectral density analysis; finally, filtering to obtain gradient-mileage i meeting road linear constraint 3 -s 3 ；
S4: conversion slope-time i 4 -t 4 A sequence;
for the slope-mileage i in the micro-stroke calculated in the step S3 3 -s 3 Merging the data, and merging the integrated gradient-mileage i 4 -s 4 Data according to mileage-time of vehicle s 1 -t 1 Data conversion to grade-time i 4 -t 4 And (6) outputting the data.
In the technical scheme, the step S1 of collecting data and establishing a database comprises the following steps:
step S1 1 : collecting road slopeDegree-related information;
road test is carried out through a vehicle-mounted GPS sensor, and time t is acquired 1 Velocity v 1 Road elevation h 1 Driving distance s 1 Data;
step S1 2 : establishing a database;
from step S1 1 Extracting time t from collected road gradient related information 1 Velocity v 1 Road elevation h 1 Driving distance s 1 The data establishes a raw Database.
In the technical scheme, the data processing in the step S2 comprises the following steps:
step S2 1 : the original data is subjected to frequency reduction to be 1Hz data;
the sampling frequency of the original data is 20Hz, and the original data is subjected to frequency reduction to be 1Hz data by using a frequency reduction method; obtaining time t of 1Hz after frequency reduction 2 Velocity v 2 Elevation h of road 2 Distance traveled s 2 Data;
step S2 2 : processing an idle speed altitude value;
because the GPS signal has noise interference, the altitude value at the idle time fluctuates, the altitude at the idle time is set as the last altitude, and the altitude is ensured to be the uniform value h in the state idle (ii) a For a driving section consisting of a plurality of micro-strokes, processing the altitude of the idle time in the sequence from back to front;
step S2 3 : dividing micro-strokes;
dividing micro-stroke according to 'starting of one section of idling to starting of next section of idling', and dividing driving section s 2 Divided into a plurality of micro-strokes s 21 ,s 22 ,s 23 ...；
Step S2 4 : merging low-speed and short-stroke micro-strokes;
according to S2 3 After the division standard is subjected to micro-travel division, the obtained result may have the highest running speed less than the minimum vehicle speed limit value v min Or the total driving range is less than the minimum range limit value s min The micro-stroke of (2); the two micro-strokes are merged to the adjacent micro-strokes, and the merging is preferentially carried out towards the previous micro-stroke.
In the technical scheme, the minimum vehicle speed limit value is not less than 0.1km/h and not more than v min ≤3km/h；
V is more than or equal to the minimum mileage limit value of 10m min ≤30m。
In the technical scheme, step S3 of calculating the slope-mileage i in the micro-stroke 3 -s 3 The method comprises the following steps:
step S3 1 : calculating slope-mileage i at 1m intervals 3 -s 3 Data;
according to GPS vehicle speed-time v 2 -t 2 And elevation h 2 Calculating the driving distance delta s and the elevation difference delta h between two adjacent sampling points according to data, and then according to a road gradient definition formula:
calculating the road slope value i corresponding to each sampling point sample Obtaining a road gradient calculation value i with a running distance interval of 1 meter by using a spline interpolation method 3 Obtaining the slope-mileage i in the micro-stroke 3 -s 3 Data;
step S3 2 : analysis of grade-Mileage i 3 -s 3 The power spectral density of the data;
analysis of grade-mile i within a single micro-trip using a power spectral density analysis function 3 -s 3 Obtaining power spectral density-frequency data pairs;
step S3 3 : cut-off frequency f of primary filter 0 ；
According to S3 2 Selecting the frequency corresponding to the upper limit value A of the total power spectral density as an initial cut-off frequency f 0 ；
Step S3 4 : grade-mileage i 3 -s 3 Data filtering;
according to S3 3 Determined cut-off frequency f 0 And constructing a zero phase shift Butterworth filter, and performing filtering processing on the slope preliminary calculation result by using the zero phase shift Butterworth filter.
Step S3 5 : judging a filtering result;
to S3 4 And (3) performing difference calculation on the calculation result, and calculating the gradient change of the road in unit distance: Δ i = i s+1 -i s (ii) a If the gradient change delta i satisfies the road alignment constraint, the filtering is ended and step S3 is executed 7 (ii) a Otherwise, executing step S3 6 ；
Step S3 6 : the cut-off frequency of the filter is attenuated;
with a certain coefficient lambda as attenuation coefficient, cut-off frequency f of filter 0 Attenuating and constructing a new filter cut-off frequency f new Filtering is carried out, and the step S3 is executed 4 ；
Step S3 7 : judging whether the road gradient calculation result exceeds a limit value i max ；
When the gradient result meets the judgment condition of finishing filtering, judging whether the gradient result exceeds a design standard limit value i of a road vertical curve max Judging; if the limit value is exceeded, step S3 is executed 8 (ii) a Otherwise, executing step S3 9 ；
Step S3 8 : processing gradient data exceeding a limit value;
design standard limit value i for exceeding road vertical curve in micro-stroke max The slope value in the micro-stroke is compressed to be within the design specification of the road vertical curve by adopting an equal proportion compression mode; compressing the gradient values exceeding +/-5% in the starting acceleration section and the deceleration stop section (defined by the driving distance of 100 meters) to +/-2% in equal proportion, and executing the step S3 7 ；
Step S3 9 : judging whether the micro-stroke is the last section of micro-stroke;
judging whether the micro-stroke is the last micro-stroke or not, if so, executing the step S4 1 Otherwise, executing step S3 10 ；
Step S3 10 : taking down a next section of micro-stroke;
selecting the next section of micro-stroke data as a calculation object, and executing the step S3 1 。
The range of the spline interpolation method in the technical scheme is 2-5 times of spline interpolation;
the upper limit value of the power spectral density is more than or equal to 95% and less than or equal to 99.9%;
the order of the zero phase shift Butterworth filter ranges from 2 to 6;
the attenuation coefficient is more than or equal to 0.9 and less than or equal to 0.99.
In the technical scheme, step S4 is carried out on the transformation gradient-time i 4 -t 4 The sequence comprises the following steps:
step S4 1 : merging the micro-stroke calculation results;
for step S3 9 The slope-mileage i in the micro-travel obtained by calculation 3 -s 3 The data are merged to obtain the gradient-mileage i of the whole travel 4 -s 4 Data;
step S4 2 : slope-time i 4 -t 4 Data conversion and output;
according to gradient-mileage i 4 -s 4 Data and mileage-time s 1 -t 1 Data is converted to obtain the road gradient-time i according to the principle that the driving distance is consistent and by combining a linear interpolation method 4 -t 4 And outputting the data as a final calculation result.
Compared with the prior art, the beneficial effects of the utility model are that:
1. compared with the conventional road gradient calculation method, the road gradient calculation method is based on the gradient calculation theory of elevation-distance ratio, the theory is easy to understand, a complex calculation formula is not needed, the calculation is convenient, and the calculation amount is small.
2. Compared with the conventional road gradient calculation method, the road gradient calculation method provided by the invention has the advantages that the required calculation data can be calculated by the low-cost vehicle-mounted GPS sensor, and the road gradient value with higher precision and suitable for the working condition design of heavy vehicles and hybrid vehicles can be calculated.
3. Compared with the conventional road gradient calculation method, the road gradient calculation method has clear calculation steps, and can be understood and implemented by a person with ordinary skill in the art without creative labor.
4. The information of the slope value calculated by the road slope calculation method is favorable for designing the correctness and the representativeness of the running working condition of the automobile containing the slope information, and is favorable for reasonably evaluating the dynamic property and the economical property of an engine and the automobile when testing is carried out based on the running working condition, so that the performance of the dynamic property and the economical property of the designed automobile on a test bed and an actual road is kept consistent.
Drawings
FIG. 1 is a diagram illustrating an exemplary implementation of a road slope calculation method based on road alignment and spectral characteristics according to the present invention;
FIG. 2 is a schematic diagram of an implementation of a zero-phase shift Butterworth filter of the road slope calculation method based on road alignment and spectral characteristics according to the present invention;
FIG. 3 is a diagram illustrating an exemplary structure of a road gradient calculation method based on road alignment and spectral characteristics according to the present invention;
FIG. 4 is a set of slope effect graphs calculated by the road slope calculation method based on road alignment and spectral features according to the present invention.
Detailed Description
The invention is described in detail below with reference to the attached drawing figures:
a road gradient calculation method based on road alignment and spectral characteristics comprises the following four parts:
first portion S1: collecting data and establishing a Database part of an original Database;
firstly, a road test is carried out by utilizing a vehicle provided with a GPS device, and then collection is carried outAnd establishing a time t 1 Velocity v 1 Road elevation h 1 Driving distance s 1 20Hz raw Database.
Second portion S2: a data primary processing part;
first, the time t in the Database is compared 1 Velocity v 1 Road elevation h 1 Driving distance s 1 Data is down-converted according to 1Hz to obtain time t of 1Hz 2 Velocity v 2 Road elevation h 2 Driving distance s 2 Data; secondly, the altitude value of the idle time (the vehicle running speed is less than 0.1m/s for two continuous seconds) is set as a uniform value h idle Then, the driving section s 2 Divided into a plurality of micro-strokes s 21 ,s 22 ,s 23 .., and finally, making the micro-stroke distance less than the set limit value s min Merge into adjacent micro-strokes.
Third portion S3: micro-stroke inner slope-mileage i 3 -s 3 Calculating;
using time t after the second part of the pretreatment 2 Velocity v 2 Road elevation h 2 Driving distance s 2 Data interpolation calculation distance interval Delta s equals to road slope value i of 1 meter 3 And for the calculated gradient i 3 The data is subjected to power spectral density analysis. Then, the set cut-off frequency f is selected 0 And the set filter F to the gradient i 3 Filtering is carried out, and then the filtered result i is 3 And (3) judging according to the road line type constraint: when the determination condition is not satisfied, the filter cut-off frequency f is set 0 Carrying out attenuation, filtering again and judging the result; when the judgment condition is met, the road gradient value i is corrected 3 Carrying out maximum value judgment, and when the maximum value is smaller than the actual limit value i of the road design max When the micro-stroke internal gradient is calculated, the calculation of the micro-stroke internal gradient is finished; when the maximum value is larger than the practical limit value i of the road design max And in time, the road gradient value in the micro-stroke is compressed in equal proportion and the maximum value is judged again.
Fourth section S4: conversion slope-time i 4 -t 4 Sequence of；
The third part calculates the slope-mileage i in the micro-stroke 3 -s 3 Merging the data, and merging the integrated gradient-mileage i 4 -s 4 Data by mileage-time s of vehicle 1 -t 1 Data conversion to grade-time i 4 -t 4 And (6) outputting the data.
The first section S1 comprises the steps of:
step S1 1 : road grade related information acquisition
Road test is carried out through a vehicle-mounted GPS sensor, and time t is acquired 1 Velocity v 1 Road elevation h 1 Driving distance s 1 And (4) data.
Step S1 2 : database establishment
From step S1 1 Extracting time t from collected road gradient related information 1 Velocity v 1 Road elevation h 1 Driving distance s 1 The data establishes a raw Database.
The second section S2 comprises the steps of:
step S2 1 : downconversion of raw data to 1Hz data
The sampling frequency of the original data is 20Hz, and the original data is subjected to frequency reduction to be 1Hz data by using a frequency reduction method. Obtaining time t of 1Hz after frequency reduction 2 Velocity v 2 Road elevation h 2 Driving distance s 2 And (4) data.
Step S2 2 : processing idle time altitude value
Since the GPS signal has noise interference, the altitude value at the idle time (the vehicle running speed is less than 0.1m/s for two continuous seconds) has fluctuation, and the fluctuation of the part needs to be processed. The altitude of the idle time is set as the altitude of the last time, and the altitude of the state is ensured to be a uniform value h idle . For a travel section composed of a plurality of micro-travels, the idle time altitude is processed in the order from the rear to the front.
Step S2 3 : micro-stroke division
And dividing the micro-stroke according to the 'starting of one section of idling to the starting of the next section of idling', and dividing the driving section into a plurality of micro-strokes.
Step S2 4 : low speed, short stroke micro-stroke merge
According to S2 3 After the division standard is subjected to micro-stroke division, the obtained result may have the highest running speed less than the minimum vehicle speed limit value v min Or the total driving range is less than the minimum range limit value s min The micro-stroke of (2). And merging the two micro-strokes into adjacent micro-strokes to calculate the road gradient, and preferentially merging the two micro-strokes one before the other during merging.
Preferably, the minimum vehicle speed limit value is more than or equal to 0.1km/h and less than or equal to vmin and less than or equal to 3km/h.
Preferably, the minimum mileage limit is 10m ≦ vmin ≦ 30m. .
The third section S3 comprises the steps of:
step S3 1 : calculating slope-mileage i at 1m intervals 3 -s 3 Data of
According to GPS vehicle speed-time v 2 -t 2 And elevation h 2 Calculating the driving distance delta s and the elevation difference delta h between two adjacent sampling points according to data, and then according to a road slope definition formula:
calculating the road slope value i corresponding to each sampling point sample Obtaining road gradient value i with 1m distance between running distances by using spline interpolation method 3 And can obtain the slope-mileage i in the micro-stroke 3 -s 3 And (4) data.
Preferably, the spline interpolation method is in the range of 2-5 spline interpolations.
Step S3 2 : grade-mileage i 3 -s 3 Power spectral density analysis of data
Analysis of grade-mile i within a single micro-trip using a power spectral density analysis function 3 -s 3 And obtaining power spectral density-frequency data pairs.
Step S3 3 : cut-off frequency f of primary filter 0
According to S3 2 Selecting the frequency corresponding to the upper limit value A of the total power spectral density as an initial cut-off frequency f 0 。
Preferably, the upper limit value of the power spectral density is more than or equal to 95% and less than or equal to 99.9%.
Step S3 4 : grade-mileage i 3 -s 3 Data filtering
According to S3 3 Determined cut-off frequency f 0 And constructing a zero phase shift Butterworth filter, and filtering the preliminary slope calculation result by using the zero phase shift Butterworth filter.
Preferably, the zero phase shift butterworth filter order ranges from 2 to 6 orders.
Step S3 5 : filter result determination
For S3 4 And (3) performing difference calculation on the calculation result, namely calculating the gradient change of the road in a unit distance: Δ i = i s+1 -i s . If the gradient change delta i satisfies the road alignment constraint, the filtering is ended and step S3 is executed 7 (ii) a Otherwise, executing step S3 6 。
Step S3 6 : filter cut-off frequency attenuation
Using a certain coefficient lambda as attenuation coefficient to cut off frequency f of filter 0 Attenuating and constructing a new filter cut-off frequency f new Filtering is carried out, and the step S3 is executed 4 。
Preferably, the attenuation coefficient is 0.9 ≦ λ ≦ 0.99.
Step S3 7 : judging whether the road gradient calculation result exceeds a limit value i max
When the gradient result meets the judgment condition of finishing filtering, judging whether the gradient result exceeds a design standard limit value i of a road vertical curve max And (6) judging. If the limit value is exceeded, step S3 is executed 8 (ii) a Otherwise, executing step S3 9 。
Step S3 8 : processing of grade data beyond limits
Design standard limit value i for exceeding road vertical curve in micro-stroke max And compressing the slope value in the micro-stroke to be within the design specification of the road vertical curve by adopting an equal proportion compression mode. Particularly, the gradient values exceeding + -5% in the starting acceleration section and the deceleration stop section (defined by the driving distance of 100 meters) are compressed to be within + -2% in equal proportion, and the step S3 is executed 7 。
Step S3 9 : judging whether the last micro-stroke is achieved
Judging whether the micro-stroke is the last micro-stroke or not, if so, executing the step S4 1 Otherwise, executing step S3 10 。
Step S3 10 : take off a little stroke
Selecting the next section of micro-stroke data as a calculation object, and executing the step S3 1 。
The fourth section S4 includes the steps of:
step S4 1 : micro-travel computation result merging
For step S3 9 The slope-mileage i in the micro-travel obtained by calculation 3 -s 3 The data are merged to obtain the gradient-mileage i of the whole travel 4 -s 4 And (4) data.
Step S4 2 : conversion into grade-time i 4 -t 4 Data output
According to gradient-mileage i 4 -s 4 Data and mileage-time s 1 -t 1 Data, according to the principle that the driving distance is consistent, a linear interpolation method is combined to obtain the road gradient-time i 4 -t 4 And outputting the data as a final calculation result.
The specific embodiment is as follows:
reference will now be made in detail to specific processes of embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to elements having like or similar functions throughout. The embodiments described below with reference to the drawings are illustrative only and should not be construed as limiting the invention.
The invention provides a road slope calculation method based on road alignment and spectrum characteristics, aiming at solving the problems that the existing road slope calculation method based on GPS information has strong dependence on GPS signals and large error of calculation results, can not be used in the working condition design of vehicles, and further influences the evaluation on the dynamic property and the economical property of the vehicles, and the method is shown in figure 1 and comprises the following four parts:
first portion S1: collecting data and establishing a Database part of an original Database;
firstly, a vehicle provided with a GPS device is used for road test, and then time t is collected and established 1 Velocity v 1 Road elevation h 1 Driving distance s 1 20Hz raw Database.
Second portion S2: a data primary processing part;
first, the time t in the Database is compared 1 Velocity v 1 Road elevation h 1 Driving mileage s 1 Data is down-converted according to 1Hz to obtain time t of 1Hz 2 Velocity v 2 Road elevation h 2 Driving distance s 2 Data; secondly, the altitude value at the idle time is set to be a uniform value h idle Then, again, the driving section s 2 Divided into a plurality of micro-strokes s 21 ,s 22 ,s 23 .., and finally, making the micro-stroke distance less than the set limit value s min Merge into adjacent micro-strokes.
Third portion S3: micro-stroke inner slope-mileage i 3 -s 3 Calculating;
using time t after the second part of the pretreatment 2 Velocity v 2 Road elevation h 2 Driving distance s 2 Road slope with data interpolation calculation distance interval delta s equal to 1 meterValue i 3 And for the calculated gradient i 3 The data were subjected to power spectral density analysis. Then, the set cut-off frequency f is selected 0 And the set filter F to the gradient i 3 Filtering is carried out, and then the filtered result i is 3 And (3) judging according to the road line type constraint: when the determination condition is not satisfied, the filter cut-off frequency f is set 0 Carrying out attenuation, filtering again and judging the result; when the judgment condition is met, the road gradient value i is corrected 3 Carrying out maximum value judgment, and when the maximum value is smaller than the actual limit value i of the road design max When the calculation of the inner gradient of the micro-stroke is finished; when the maximum value is larger than the practical limit value i of the road design max And compressing the road gradient value in the section of the micro-stroke in equal proportion and judging the maximum value again.
Fourth section S4: transforming a gradient-time i4-t4 sequence;
the third part calculates the slope-mileage i in the micro-stroke 3 -s 3 Merging the data, and merging the integrated gradient-mileage i 4 -s 4 Data according to mileage-time of vehicle s 1 -t 1 Data conversion to grade-time i 4 -t 4 And (6) outputting data.
The first section S1 comprises the steps of:
step S1 1 : road grade related information acquisition
Road test is carried out through a vehicle-mounted GPS sensor, and time t is acquired 1 Velocity v 1 Road elevation h 1 Driving distance s 1 And (4) data.
Step S1 2 : database establishment
From step S1 1 Extracting time t from collected road gradient related information 1 Velocity v 1 Road elevation h 1 Driving distance s 1 The data establish a 20Hz raw Database.
The second section S2 comprises the steps of:
step S2 1 : down-conversion of raw data to 1Hz data
The sampling frequency of the original data is 20Hz, and the original data is subjected to frequency reduction to be 1Hz data by using a frequency reduction method. Obtaining time t of 1Hz after frequency reduction 2 Velocity v 2 Road elevation h 2 Driving distance s 2 And (4) data.
Step S2 2 : processing idle time altitude value
Since the GPS signal has noise interference, the altitude value at the idle time (the vehicle running speed is less than 0.1m/s for two continuous seconds) has fluctuation, and the fluctuation of the part needs to be processed. The altitude at the idle time is set as the altitude at the last time, and the altitude in the state is ensured to be a uniform value h idle . For a travel section composed of a plurality of micro-travels, the idle time altitude is processed in the order from the rear to the front.
Step S2 3 : micro-stroke division
And dividing the micro-stroke according to the 'starting of one section of idling to the starting of the next section of idling', and dividing the driving section into a plurality of micro-strokes. For example two adjacent idle speed sections, the time of the preceding section being [ t ] p+1 ,t p+2 ,t p+3 …,t p+m ]The time of the latter segment is [ t ] k+1 ,t k+2 ,t k+3 ,…,t k+n ]Wherein t is k+1 -t p+m >, 2, mixing [ t ] p+1 ,t p+2 ,t p+3 …,t p+m ,…,t k+1 ]The inner data is divided into one micro-trip.
Step S2 4 : low speed, low stroke micro-stroke merge
According to S2 3 After the division standard is subjected to micro-stroke division, the obtained result may have the highest running speed less than the minimum vehicle speed limit value v min Or the total driving range is less than the minimum range limit value s min According to the data acquisition quality, the vehicle speed limit value is greater than or equal to 0.1km/h and less than or equal to 3km/h, and the vehicle speed limit value v min Preferably 1km/h; the mileage limit is selected to be greater than or equal to 10m and less than or equal to 30m, and the mileage limit s min Preferably 20 meters. The two micro-strokes are combined into an adjacent micro-stroke to calculate the road gradient, and the combination is preferentially carried outThe previous micro-trip merges.
The third section S3 comprises the steps of:
step S3 1 : calculating slope-mileage i at 1m intervals 3 -s 3 Data of
According to GPS vehicle speed-time v 2 -t 2 And elevation h 2 Calculating the driving distance delta s and the elevation difference delta h between two adjacent sampling points according to data, and then according to a road gradient definition formula:
calculating the road slope value i corresponding to each sampling point sample Obtaining road gradient value i with 1m distance between running distances by using spline interpolation method 3 Obtaining the slope-mileage i in the micro-stroke 3 -s 3 And (4) data. The spline interpolation method can be selected from 2-5 times of spline interpolation, preferably 3 times of spline interpolation according to the calculation precision requirement.
Step S3 2 : grade-mileage i 3 -s 3 Power spectral density analysis of data
Analysis of grade-mile i within a single micro-trip using a power spectral density analysis function 3 -s 3 And obtaining power spectral density-frequency data pairs.
Step S3 3 : cut-off frequency f of primary filter 0
According to the power spectral density analysis result of the slope calculated value, selecting the frequency corresponding to the upper limit value A of the total power spectral density as an initial cut-off frequency f 0 The upper limit value a of the power spectral density is selected to be greater than or equal to 95%, and less than or equal to 99.9%, for example, the upper limit value of the power spectral density is selected to be 99%, according to the requirements of computational efficiency and accuracy.
Step S3 4 : slope-mileage data filtering
According to S3 3 Determined cut-off frequency f 0 Constructing zero-phase-shift Butterworth filters, using zero-phase-shift Butterworth filtersAnd filtering the preliminary slope calculation result, wherein the order of the zero-phase shift Butterworth filter is selected to be greater than or equal to 2 orders, less than or equal to 6 orders and preferably 4 orders according to the calculation efficiency and precision requirements.
Referring to fig. 2, the filtering process of the zero-phase shift butterworth filter is: firstly, carrying out forward filtering on a gradient preliminary calculation result; secondly, performing time domain turnover on the filtered result; thirdly, forward filtering is carried out on the sequence after the inversion; and finally, performing time domain turnover on the result after the filtering of the filter for the second time and outputting a gradient-mileage i-s sequence.
Step S3 5 : filter result determination
To S3 4 And (3) performing difference calculation on the calculation result, namely calculating the gradient change of the road in a unit distance: Δ i = i s+1 -i s . If the slope change Δ i satisfies the road alignment constraint, for example: designing a road with the speed of 80km/h, wherein the radius of a vertical curve of the road is 2000 m at the minimum, the gradient change rate at the interval of 1m is less than 1/2000, if the constraint condition is met, finishing filtering, and executing a step S3 7 (ii) a Otherwise, executing step S3 6 。
Step S3 6 : filter cut-off frequency attenuation
With a certain coefficient lambda as attenuation coefficient, cut-off frequency f of filter 0 Attenuating and constructing a new filter cut-off frequency f new Filtering is carried out, and the step S3 is executed 4 The attenuation factor λ is chosen to be greater than or equal to 0.9, less than or equal to 0.99, preferably 0.95, depending on computational efficiency and accuracy requirements.
Step S3 7 : judging whether the road gradient calculation result exceeds a limit value i max
When the gradient result meets the judgment condition of finishing filtering, judging whether the gradient result exceeds a design standard limit value i of a road vertical curve max And (4) judging, wherein the road slope limit value in the expressway data is +/-5 percent. If the limit value is exceeded, step S3 is executed 8 (ii) a Otherwise, executing step S3 9 。
Step S3 8 : processing of slope data exceeding a limit
Design standard limit value i for exceeding road vertical curve in micro-stroke max And compressing the slope value in the micro-stroke to be within the design specification of the road vertical curve by adopting an equal proportion compression mode. Particularly, the gradient values exceeding + -5% in the starting acceleration section and the deceleration stop section (defined by the driving distance of 100 meters) are compressed to be within + -2% in equal proportion, and the step S3 is executed 7 。
Step S3 9 : judging whether the last micro-stroke is achieved
Judging whether the micro-stroke is the last micro-stroke or not, if so, executing the step S4 1 Otherwise, executing step S3 10 。
Step S3 10 : take down a little stroke
Selecting the next section of micro-stroke data as a calculation object, and executing the step S3 1 。
The fourth section S4 includes the steps of:
step S4 1 : micro-travel computation result merging
For step S3 9 Calculating the gradient-mileage i in the micro-travel 3 -s 3 The data are merged to obtain the gradient-mileage i of the whole travel 4 -s 4 And (4) data.
Step S4 2 : gradient-time i4-t4 data conversion and output
According to gradient-mileage i 4 -s 4 Data and mileage-time s 1 -t 1 Data, according to the principle that the driving distance is consistent, a linear interpolation method is combined to obtain the road gradient-time i 4 -t 4 And outputting the data as a final calculation result.
Corresponding to the road slope calculation method based on the road alignment and the spectral characteristics of the invention, referring to fig. 3, the road slope calculation module 1 based on the road alignment and the spectral characteristics of the invention comprises a road slope calculation process module 2, a speed and elevation data module 3, a national standard road slope data module 4, a road section forming point slope calculation module 5, an idle point and road section extraction and splitting module 6, a power spectral density and road line type analysis module 7, a slope data power spectral density analysis module 8, a slope data zero phase shift filter module 9, a slope data change rate judgment module 10, a maximum value judgment module 11 of slope data, and a slope data merging and outputting module 12.
The module 3 is a speed and elevation data module, a GPS sensor is installed on the experimental vehicle, information such as vehicle speed and elevation is collected, and a database used for calculating the gradient of the whole road is constructed. The module 5 is a slope calculation module for road section forming points, and calculates the slope value of the road section forming points by using a slope calculation formula of elevation and distance ratio. The module 6 is a module for extracting idle points and splitting road sections, and comprises the steps of extracting road sections at the idle time of the vehicle and splitting gradient data according to the idle road sections. The module 7 is a power spectral density and road line type analysis module which is a main part of the whole algorithm and comprises a module 8 gradient data power spectral density analysis module for carrying out power spectral density analysis on gradient-mileage data in a micro-stroke; a module 9, a slope data zero phase shift filtering module, which is used for performing zero phase shift filtering on the slope-mileage data in the micro-stroke according to the power spectral density analysis result of the module 8; the module 10 is a slope data change rate judging module which judges the change rate of the slope-mileage data filtered by the module 9 according to the highway slope data in the national standard of the module 4; and the module 11 is a maximum value judging module for judging the maximum value of the gradient-mileage data after the change rate of the module 10 is judged according to the road gradient data in the national standard of the module 4. The module 12 is a slope data merging and outputting module, and merges the slope-mileage data in the micro-trip calculated by the module 7 to obtain the slope-mileage data of the whole trip, then determines the road slope at the moment according to the mileage-time data, and obtains and outputs the calculated road slope-time sequence.
The embodiments in this specification are described in a progressive manner, and the same and similar parts between the respective embodiments may be referred to each other. In particular, for the structural embodiment, since it is basically similar to the method implementation process, the description is simple, and the relevant points can be referred to the partial description of the method implementation process. The above-described structural embodiments are merely illustrative, and the modules and units described as separate components may or may not be physically separate, may be located in one position, or may be distributed on a plurality of network units. Some or all of the modules and units can be selected according to actual needs to implement the scheme and the purpose of the embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
The present invention is not limited to the embodiments shown in the drawings, and all modifications and equivalents thereof that are made according to the spirit and scope of the present invention are intended to be covered by the claims.
Claims (7)
1. A road gradient calculation method based on road alignment and spectral characteristics is characterized by comprising the following steps:
s1: collecting data and establishing an original Database;
s2: processing data;
reducing the frequency of data in the Database, and setting the altitude value at idle speed as a uniform value h idle The idle time is defined as that the running speed of the vehicle is less than 0.1m/s for two continuous seconds, the running section is divided into a plurality of micro-strokes, and the micro-stroke distance is less than a set limit value s min Merging the micro-strokes into adjacent micro-strokes;
s3: calculating slope-mileage i in micro-stroke 3 -s 3 ；
Firstly, calculating a gradient value i with road mileage interval of 1 meter according to the data processed in the step S2 3 (ii) a Secondly, for the gradient value i 3 Performing power spectral density analysis; finally, filtering to obtain gradient-mileage i meeting road linear constraint 3 -s 3 ；
S4: conversion slope-time i 4 -t 4 A sequence;
for the slope-mileage i in the micro-stroke calculated in the step S3 3 -s 3 Merging the data, and merging the integrated gradient-mileage i 4 -s 4 Data according to mileage-time of vehicle s 1 -t 1 Data conversion to grade-time i 4 -t 4 And (6) outputting the data.
2. The road gradient calculation method based on road alignment and spectral features according to claim 1, characterized in that:
the step S1 of collecting data and establishing a database comprises the following steps:
step S1 1 : collecting road gradient related information;
road test is carried out through a vehicle-mounted GPS sensor, and time t is acquired 1 Velocity v 1 Road elevation h 1 Driving distance s 1 Data;
step S1 2 : establishing a database;
from step S1 1 Extracting time t from collected road gradient related information 1 Velocity v 1 Road elevation h 1 Driving distance s 1 The data establishes a raw Database.
3. The road gradient calculation method based on road alignment and spectral features according to claim 1, characterized in that:
the processing data of step S2 includes the following steps:
step S2 1 : the original data is subjected to frequency reduction to be 1Hz data;
the sampling frequency of the original data is 20Hz, and the original data is subjected to frequency reduction to be 1Hz data by using a frequency reduction method; obtaining time t of 1Hz after frequency reduction 2 Velocity v 2 Elevation h of road 2 Distance traveled s 2 Data;
step S2 2 : processing an idle speed altitude value;
because the GPS signal has noise interference, the altitude value at the idle time fluctuates, the altitude at the idle time is set as the last altitude, and the altitude is ensured to be the uniform value h in the state idle (ii) a For a driving section consisting of a plurality of micro-strokes, processing the altitude of the idle time in the sequence from back to front;
step S2 3 : dividing micro-strokes;
dividing micro-travel according to 'starting of one section of idling to starting of next section of idling', and dividing the travel section s 2 Divided into a plurality of micro-strokes s 21 ,s 22 ,s 23 ...；
Step S2 4 : merging low-speed and short-stroke micro-strokes;
according to S2 3 After the division standard is subjected to micro-stroke division, the obtained result may have the highest running speed less than the minimum vehicle speed limit value v min Or the total driving range is less than the minimum range limit value s min The micro-stroke of (2); the two micro-strokes are merged to the adjacent micro-strokes, and the merging is preferentially carried out towards the previous micro-stroke.
4. The road gradient calculation method based on road alignment and spectral features according to claim 3, characterized in that:
the minimum vehicle speed limit value is less than or equal to v and less than or equal to 0.1km/h min ≤3km/h；
V is more than or equal to the minimum mileage limit value of 10m min ≤30m。
5. The road gradient calculation method based on road alignment and spectral features according to claim 1, characterized in that:
step S3, calculating the slope-mileage i in the micro-stroke 3 -s 3 The method comprises the following steps:
step S3 1 : calculating slope-mileage i at 1m intervals 3 -s 3 Data;
according to GPS vehicle speed-time v 2 -t 2 And elevation h 2 Between two adjacent sampling points of data calculationThe driving distance deltas and the elevation difference deltah are defined according to the road gradient:
calculating the road slope value i corresponding to each sampling point sample Obtaining a road gradient calculation value i with a running distance interval of 1 meter by using a spline interpolation method 3 Obtaining the slope-mileage i in the micro-stroke 3 -s 3 Data;
step S3 2 : analysis of grade-Mileage i 3 -s 3 The power spectral density of the data;
analysis of grade-mile i within a single micro-trip using a power spectral density analysis function 3 -s 3 Data, obtaining power spectral density-frequency data pairs;
step S3 3 : cut-off frequency f of primary filter 0 ；
According to S3 2 Selecting the frequency corresponding to the upper limit value A of the total power spectral density as an initial cut-off frequency f 0 ；
Step S3 4 : grade-mileage i 3 -s 3 Data filtering;
according to S3 3 Determined cut-off frequency f 0 Constructing a zero phase shift Butterworth filter, and performing filtering processing on the slope preliminary calculation result by using the zero phase shift Butterworth filter;
step S3 5 : judging a filtering result;
to S3 4 And (3) performing difference calculation on the calculation result, and calculating the gradient change of the road in unit distance: Δ i = i s+1 -i s (ii) a If the gradient change delta i satisfies the road alignment constraint, the filtering is ended and step S3 is executed 7 (ii) a Otherwise, executing step S3 6 ；
Step S3 6 : the cut-off frequency of the filter is attenuated;
with a certain coefficient lambda as attenuation coefficient, cut-off frequency f of filter 0 Attenuating and constructing a new filter sectionStop frequency f new Filtering is carried out, and the step S3 is executed 4 ；
Step S3 7 : judging whether the road gradient calculation result exceeds a limit value i max ；
When the gradient result meets the judgment condition of finishing filtering, judging whether the gradient result exceeds a design standard limit value i of a road vertical curve max Judging; if the limit value is exceeded, step S3 is executed 8 (ii) a Otherwise, executing step S3 9 ；
Step S3 8 : processing gradient data exceeding a limit value;
limit value i of vertical curve design specification exceeding road in micro-stroke max The slope value in the micro-stroke is compressed to be within the design specification of a road vertical curve by adopting an equal proportion compression mode; compressing gradient values exceeding +/-5% in a starting acceleration section and a deceleration parking section to +/-2% in an equal proportion, defining the starting acceleration section and the deceleration parking section by a driving distance of 100 meters, and executing a step S3 7 ；
Step S3 9 : judging whether the micro-stroke is the last section of micro-stroke;
judging whether the micro-stroke is the last micro-stroke or not, if so, executing the step S4 1 Otherwise, executing step S3 10 ；
Step S3 10 : taking a next section of micro-stroke;
selecting the next section of micro-stroke data as a calculation object, and executing the step S3 1 。
6. The road gradient calculation method based on road alignment and spectral features according to claim 5, characterized in that:
the spline interpolation method is in the range of 2-5 times spline interpolation;
the upper limit value of the power spectral density is more than or equal to 95% and less than or equal to 99.9%;
the order range of the zero phase shift Butterworth filter is 2-6 orders;
the attenuation coefficient is more than or equal to 0.9 and less than or equal to 0.99.
7. The road gradient calculation method based on road alignment and spectral features according to claim 1, characterized in that:
step S4, the conversion gradient-time i 4 -t 4 The sequence comprises the following steps:
step S4 1 : merging the micro-stroke calculation results;
for step S3 9 The slope-mileage i in the micro-travel obtained by calculation 3 -s 3 Merging the data to obtain the slope-mileage i of the whole travel 4 -s 4 Data;
step S4 2 : slope-time i 4 -t 4 Data conversion and output;
according to gradient-mileage i 4 -s 4 Data and mileage-time s 1 -t 1 Data is converted to obtain the road gradient-time i according to the principle that the driving distance is consistent and by combining a linear interpolation method 4 -t 4 And outputting the data as a final calculation result.
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