CN111806450A - Road spectrum data processing method and power matching method based on actual operation road - Google Patents
Road spectrum data processing method and power matching method based on actual operation road Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
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- B60W40/02—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 ambient conditions
- B60W40/06—Road conditions
- B60W40/076—Slope angle of the road
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
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- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
- B60W2520/105—Longitudinal acceleration
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- B—PERFORMING OPERATIONS; TRANSPORTING
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- B60W2552/00—Input parameters relating to infrastructure
- B60W2552/05—Type of road, e.g. motorways, local streets, paved or unpaved roads
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2555/00—Input parameters relating to exterior conditions, not covered by groups B60W2552/00, B60W2554/00
- B60W2555/40—Altitude
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Abstract
The invention discloses a road spectrum data processing method and a power matching method based on an actual operation road, and relates to the technical field of automobiles.
Description
Technical Field
The invention relates to the technical field of automobiles, in particular to a road spectrum data processing method and a power matching method based on actual operation roads.
Background
With the rapid development of new energy vehicles, the coverage range of an operation route of a new energy vehicle is wider and wider, and the method is particularly important for obtaining road information such as the gradient of a local actual operation route and matching the power system based on the road information so as to meet the requirements of the whole vehicle dynamic property and economy of each specific operation route as much as possible and reduce the purchasing cost of the whole vehicle as much as possible without excessive surplus or insufficient power of the matched power system.
The patent application document with the Chinese patent application number of CN106370435A discloses a road spectrum acquisition system, a vehicle and a road spectrum acquisition method, and the main technical scheme is to design the road spectrum acquisition system which comprises a GPS receiving device, a scanning device and a processing device and can improve the data acquisition precision. The invention mainly aims at the acquisition of the road spectrum data. The corresponding processing method of road spectrum and the elimination of error data are not introduced.
The patent application document with the Chinese invention patent application number of CN201710945169.8 discloses a vehicle power matching method, a device, equipment and a storage medium, wherein a plurality of corresponding motor parameter values and a plurality of corresponding battery parameter values are determined according to the performance indexes of the whole vehicle, and a plurality of combination forms are obtained; and carrying out economic simulation on the operating conditions and the combined schemes through simulation software to determine the optimal matching scheme of the power system.
In summary, it is necessary to design a processing method based on road spectrum data of a road on which a vehicle is actually operated, calculate and obtain more accurate road information such as road mileage, gradient change rate and the like, and then use the road information to perform power system matching on the vehicle, so as to check feasibility of a power matching scheme.
Disclosure of Invention
The invention provides a road spectrum data processing method and a power matching method based on actual operation roads, and mainly aims to solve the problems.
The invention adopts the following technical scheme:
a road spectrum data processing method based on actual operation roads specifically comprises the following steps.
1. And road spectrum data acquisition is carried out on the actual operation route by adopting road spectrum acquisition equipment, and data preprocessing is carried out.
2. And calculating the theoretical gradient of the actual operation route according to a formula i = (h/L) × 100% by using road spectrum data, and establishing a theoretical time domain gradient i (t), wherein L is the plane distance between two points of the actual operation route, and h is the altitude difference between the two points of the actual operation route.
3. And carrying out error processing on the data of the theoretical time domain gradient i (t), wherein the error processing comprises the following substeps.
3.1, determining the type of the actual operation road and determining the maximum gradient reference value i0 +/-0 of the road, wherein i0Is a reference value of the gradient, and0is an empirical deviation value.
And 3.2, carrying out fast Fourier transform on the theoretical time domain gradient i (t) to obtain a frequency domain gradient signal.
And 3.3, selecting a proper filtering method to filter the frequency domain gradient signal in the step 3.2, and reducing the error.
3.4, performing inverse fast Fourier transform on the filtered frequency domain gradient signal to obtain a time domain gradient i1(t), the following error data reprocessing is performed.
When i is1(t)>i0±0And t is<t0When i is1(t)=iorgWhere t denotes a vehicle running time corresponding to a slope, t0Indicating the initial starting time, iorgThe initial value of the gradient of the vehicle at the initial starting stage is obtained.
When i is1(t)>i0±0And t is more than or equal to t0When the temperature of the water is higher than the set temperature,
in the formula, t represents the vehicle running time corresponding to the slope, (t) is a weight coefficient, and t2As time domain slope i1(t) a starting time at which the maximum slope limit is exceeded, t1For a selected point in time before the start of the maximum slope limit, and t2＞t1≥t0。
3.5, repeating the step 3.3 and the step 3.4 until i1(t)≤i0±0Ending and outputting the finally obtained time domain gradient i2(t)。
Further, a suitable filtering method in step 3.3 is specifically: if the larger error is only in the low frequency range, high-pass filtering is preferred; if the error only appears in the high frequency region, low pass filtering is preferred; if both high and low frequencies are present, then bandpass filtering is preferred.
Further, in the step 3.1, the type of the actual operation road is determined according to the technical standard of highway engineering; and then combining the technical standard of road engineering and commercial satellite map software to obtain the maximum gradient reference value i of the road section0±0。
Further, in step 3.2, the theoretical time domain gradient i (t) is fast fourier transformed by using the following formula.
Wherein k is the number of sampled signals, k =0,1,2,... times.n-1;
x (N) is a sampled time domain slope signal, N is the number of sampled signals, N =0,1, 2.
A power matching method based on an actual operation road is characterized by comprising the following steps.
A. Road spectrum data of an actual operation route is obtained by the road spectrum data processing method as claimed in any one of the preceding claims, and a time domain gradient i is obtained at the same time2(t)。
B. According to the continuous running time length, the speed, the acceleration, the mileage of the vehicle and the gradient data i2And (t) matching and calculating the power system by combining the corresponding relation between the real vehicle parameters and the real vehicle parameters to obtain the real-time parameter indexes of the motor and the related indexes of the power battery.
C. And B, checking the power matching scheme in the step B based on real-time rotating speed-torque, rotating speed-power and motor performance test data of the motor obtained under the road spectrum working condition to obtain an optimal power matching scheme.
Further, in the step C, when the power matching scheme in the step B is checked, the ratio of unsatisfied demand indexes is output, and the motor system efficiency is considered to determine the motor system scheme; and then determining a power battery voltage platform according to the motor system voltage platform, determining the discharge power, the discharge current, the charge power, the charge current and the battery capacity when the battery charge-discharge efficiency is maximum according to the road spectrum data of the actual operation road, and further checking the power battery scheme.
Further, in the step C, the motor system scheme is specifically checked as follows.
And C.1, importing power characteristic data of the motor, and solving the number of the power demand data obtained according to the road spectrum data, which is larger than the number of the data matched with the power characteristic of the motor, namely the number of the power demand data which does not meet the road spectrum.
And C.2, calculating the proportion of the unsatisfied demand power data in the whole demand power data.
C.3 setting threshold value w0When the specific gravity is not less than w when the road spectrum power requirement is not met0Then the motor is deemed to be not meeting the requirements.
C.4, setting the percentage threshold of the motor system efficiency higher than 85% as w1。
C.5, when the specific gravity does not meet the road spectrum power requirement is less than the threshold value w0And if the proportion of the motor system efficiency higher than 85% is larger than or equal to the threshold value w1, the motor is considered to meet the requirement.
Further, the method also comprises the step D: and verifying the speed following condition of the optimal power matching scheme by combining system simulation software according to the data of mileage, gradient and time and speed, and further checking the feasibility of the optimal power matching scheme.
Compared with the prior art, the invention has the beneficial effects that:
the invention aims to provide a road spectrum data processing method and a power matching method based on an actual operation road, more accurate road spectrum data can be obtained through the road spectrum data processing method, particularly error gradient data is processed, then a vehicle power scheme meeting the actual operation road is quickly matched according to the processed road spectrum data, waste in the aspects of cost, manpower and the like caused by excessive surplus or insufficient power is reduced to the maximum extent, and meanwhile, driving safety is improved.
Drawings
Fig. 1 is a flowchart of a road spectrum data processing method according to the present invention.
FIG. 2 is a flow chart of a power matching method of the present invention.
Detailed Description
The following describes embodiments of the present invention with reference to the drawings. Numerous details are set forth below in order to provide a thorough understanding of the present invention, but it will be apparent to those skilled in the art that the present invention may be practiced without these details.
As shown in fig. 1, a road spectrum data processing method based on an actual operation road specifically includes the following steps:
1. and road spectrum data acquisition is carried out on the actual operation route by adopting road spectrum acquisition equipment, and data preprocessing is carried out.
Wherein, the data that road spectrum collection equipment gathered mainly contains: latitude and longitude, local time, vehicle speed, and altitude. The data preprocessing mainly comprises the following steps: 1) the local time is converted into a continuous time duration. That is, the local time collected by the road spectrum collecting device is firstly differentiated to obtain the time interval between each two adjacent points, and then the time intervals are summed to obtain the continuous time. The continuous time is used for subsequently processing acceleration, altitude, vehicle speed, gradient and other data and establishing time domain signals of all the data; 2) acquiring required complete road longitude and latitude data from the acquired data; and converting the longitude and latitude coordinates into Gaussian plane coordinates, and calculating the plane distance L of any two points of the spherical surface.
2. And calculating the theoretical gradient of the actual operation route according to a formula i = (h/L) × 100% by using the road spectrum data, and then establishing a theoretical time-domain gradient i (t). In the formula, L is the plane distance between two points of the actual operation route, and is obtained by 2) calculation, h is the altitude difference between the two points of the actual operation route, and the altitude and the local time acquired by the road spectrum acquisition equipment are utilized to establish the altitude time domain signal of the actual operation route and obtain the altitude difference h.
3. And carrying out error processing on the data of the theoretical time domain gradient i (t). The road spectrum acquisition equipment is used for acquiring distorted elevation data on road sections such as bridges, tunnels, annular roads and the like due to communication problems, so that the theoretical gradient i calculated by using a formula i = (h/L) × 100% has larger errors on the road sections. Therefore, error processing needs to be performed on the data of the theoretical time domain slope i (t), so as to improve the accuracy of the data, which is specifically as follows:
3.1 determining the data acquisition road type. Specifically, the actual operation route types (such as expressways, first-level roads, second-level roads, third-level roads and the like) are determined according to the technical standards of highway engineering; and then combining the technical standard of highway engineering and commercial satellite map software to obtain the maximum gradient reference value i of the road0±0Wherein the gradient reference value i0For reference values obtained by a combination of both "Standard" and commercial software0Is an empirical deviation value.
3.2 performing fast Fourier transform on the theoretical time domain gradient i (t) established in the step 3. Specifically, the theoretical time-domain slope i (t) is fast fourier transformed using the following equation:
wherein k is the number of sampled signals, k =0,1,2,... times.n-1;
x (k) represents frequency domain gradient data after fast fourier transform, x (N) is a sampled time domain gradient signal, N is the number of sampled signals, N =0,1, 2.
And converting the theoretical time domain signal of the gradient into a frequency domain signal by the formula of the fast Fourier transform, and observing the range of the error with the larger gradient.
3.3 according to the error condition of the gradient data, selecting a proper filtering method to process the frequency domain gradient signal obtained by the fast Fourier transform in the step 3.2, and reducing the error. Specifically, 1) if the large error is only in the low frequency range, high-pass filtering is preferable, and 2) if the error is only in the high frequency region, low-pass filtering is preferable; 3) if both high and low frequencies are present, then bandpass filtering is preferred. In addition, the expected effect cannot be achieved by only one filtering in general data processing, and then methods such as median filtering and Kalman filtering can be combined, which are mainly determined according to the road spectrum condition of the actual operation route.
3.4 the filtered frequency domain gradient signal is subjected to fast Fourier inverse transformation to obtain a time domain gradient i1(t), error data reprocessing is performed, specifically as follows:
3.4.1 when i1(t)>i0±0And t is<t0When i is1(t)=iorgT represents a vehicle running time corresponding to a slope, t0Indicating the initial starting time, iorgThe initial value of the gradient of the vehicle at the initial starting stage is measured by a gradiometer. The default gradient data acquisition starting moment is located on a non-ramp road on a section of flat road, and if a large gradient occurs at the initial moment, the error of the altitude data acquired by the equipment is considered to be caused. Thus, for time domain slope i1(t) at a vehicle running time t0Data preceding and exceeding the maximum grade reference limit is taken i1(t)=iorgCorrecting; for example, a smooth road section of 200m or more is specified at the start of data acquisition, and t is estimated according to the running condition of the real vehicle0If the vehicle is driven at a constant speed of 20km/h in the initial starting stage, t is0About 35 s. i.e. iorgThe initial value of the road measured by the gradiometer is the initial time.
3.4.2 when i1(t)>i0±0And t is more than or equal to t0When the temperature of the water is higher than the set temperature,
in the above formula, t represents the vehicle running time corresponding to the slope, (t) is a weight coefficient, and t2As time domain slope i1(t) a starting time at which the maximum slope limit is exceeded, t1For a selected point in time before the start of the maximum slope limit, and t2＞t1≥t0。
3.5 repeat step 3.3 and step 3.4 until i1(t)≤i0±0Ending and outputting the finally obtained time domain gradient i2(t)。
As shown in fig. 1 and 2, a power matching method based on an actual operation road includes the following steps:
A. the road spectrum data of the actual operation route is obtained through the road spectrum data processing method, and meanwhile, the time domain gradient i is obtained2(t)。
B. And outputting the whole vehicle power index based on the road spectrum data of the actual operation road. According to the continuous running time length, the speed, the acceleration, the mileage of the vehicle and the gradient data i2And (t) matching and calculating the power system by combining the corresponding relation between the real vehicle parameters and the real vehicle parameters to obtain the real-time parameter indexes of the motor and the relevant indexes of the power battery.
C. And checking the multiple power matching schemes one by one. Checking a power matching scheme based on real-time motor rotating speed-torque, rotating speed-power and motor performance test data obtained under the road spectrum working condition, outputting the ratio which does not meet the requirement index, and determining a motor system scheme by considering the motor system efficiency; and determining a power battery voltage platform according to the motor system voltage platform, determining the discharge power, the discharge current, the charge power, the charge current and the battery capacity when the battery charge-discharge efficiency is maximum according to the road spectrum data of the actual operation road, and further checking the power battery scheme to obtain an optimal power matching scheme (the power matching scheme comprises a motor system scheme and a power battery scheme). The specific method for checking the scheme of the motor system comprises the following steps:
and C.1, importing power characteristic data of the motor, and solving the problem that the power demand data obtained according to the road spectrum data (namely the road spectrum data of the actual operation road) is more than the number of data matched with the power characteristic of the motor, namely the number of the data which do not meet the road spectrum power demand.
And C.2, calculating the proportion of the unsatisfied demand power data in the whole demand power data.
C.3 setting threshold value w0When the specific gravity is not less than w when the road spectrum power requirement is not met0Then the motor is considered notThe requirement is met, and the scheme of the motor system is eliminated.
C.4, setting the percentage threshold of the motor system efficiency higher than 85% as w1。
C.5, when the specific gravity does not meet the road spectrum power requirement is less than the threshold value w0And the ratio of the motor system efficiency higher than 85 percent is more than or equal to the threshold value w1And if so, the motor is considered to meet the requirement, and the motor system scheme is selected.
D. According to the mileage-gradient and time-speed data, speed following conditions of the optimal power matching scheme are verified by combining system simulation software (such as AVLcruise, AMEstim or Simulink), and feasibility of the optimal power matching scheme is further checked.
The above description is only an embodiment of the present invention, but the design concept of the present invention is not limited thereto, and any insubstantial modifications made by using the design concept should fall within the scope of infringing the present invention.
Claims (8)
1. The road spectrum data processing method based on the actual operation road specifically comprises the following steps: 1. road spectrum data acquisition is carried out on the actual operation route by adopting road spectrum acquisition equipment, and data preprocessing is carried out; 2. calculating a theoretical gradient of an actual operation route according to a formula i = (h/L) × 100% by using road spectrum data, and establishing a theoretical time domain gradient i (t), wherein L is a plane distance between two points of the actual operation route, and h is an altitude difference between the two points of the actual operation route; the method is characterized by further comprising the following steps:
3. error processing is carried out on the data of the theoretical time domain gradient i (t), and the error processing method comprises the following sub-steps:
3.1, determining the type of the actual operation road and determining the maximum gradient reference value i of the road0±0Wherein i is0Is a reference value of the gradient, and0the empirical deviation value is obtained;
3.2, carrying out fast Fourier transform on the theoretical time domain gradient i (t) to obtain a frequency domain gradient signal;
3.3, selecting a proper filtering method to filter the frequency domain gradient signal in the step 3.2, and reducing errors;
3.4, performing inverse fast Fourier transform on the filtered frequency domain gradient signal to obtain a time domain gradient i1(t), error data reprocessing is performed as follows:
when i is1(t)>i0±0And t is<t0When i is1(t)=iorgWhere t denotes a vehicle running time corresponding to a slope, t0Indicating the initial starting time, iorgThe initial value of the gradient of the vehicle at the initial starting stage;
when i is1(t)>i0±0And t is more than or equal to t0When the temperature of the water is higher than the set temperature,
in the formula, t represents the vehicle running time corresponding to the slope, (t) is a weight coefficient, and t2As time domain slope i1(t) a starting time at which the maximum slope limit is exceeded, t1For a selected point in time before the start of the maximum slope limit, and t2＞t1≥t0；
3.5, repeating the step 3.3 and the step 3.4 until i1(t)≤i0±0Ending and outputting the finally obtained time domain gradient i2(t)。
2. The road spectrum data processing method based on actual service roads according to claim 1, wherein: suitable filtering methods in step 3.3 are specifically: if the larger error is only in the low frequency range, high-pass filtering is preferred; if the error only appears in the high frequency region, low pass filtering is preferred; if both high and low frequencies are present, then bandpass filtering is preferred.
3. The road spectrum data processing method based on actual service roads according to claim 1, wherein: in the step 3.1, the type of the actual operation route is determined according to the technical standard of highway engineering; and then combining the technical standard of road engineering and commercial satellite map software to obtain the maximum gradient reference value i of the road section0±0。
4. The road spectrum data processing method based on actual service roads according to claim 1, wherein: in the step 3.2, the following formula is used to perform fast fourier transform on the theoretical time domain gradient i (t):
wherein k is the number of sampled signals, k =0,1,2,... times.n-1;
x (N) is a sampled time domain slope signal, N is the number of sampled signals, N =0,1, 2.
5. A power matching method based on an actual operation road is characterized by comprising the following steps:
A. road spectrum data of an actual service route are obtained by the road spectrum data processing method as claimed in any one of claims 1 to 4, and a time domain gradient i is obtained at the same time2(t)。
B. According to the continuous running time length, the speed, the acceleration, the mileage of the vehicle and the gradient data i2(t) matching and calculating the power system by combining the corresponding relation between the real vehicle parameters to obtain the real-time parameter index of the motor and the related index of the power battery;
C. and B, checking the power matching scheme in the step B based on real-time rotating speed-torque, rotating speed-power and motor performance test data of the motor obtained under the road spectrum working condition to obtain an optimal power matching scheme.
6. The power matching method based on the actual operation road according to claim 5, wherein: in the step C, when the power matching scheme in the step B is checked, outputting the ratio which does not meet the requirement index, and determining the scheme of the motor system by considering the efficiency of the motor system; and then determining a power battery voltage platform according to the motor system voltage platform, determining the discharge power, the discharge current, the charge power, the charge current and the battery capacity when the battery charge-discharge efficiency is maximum according to the road spectrum data of the actual operation road, and further checking the power battery scheme.
7. The power matching method based on the actual operation road as claimed in claim 6, wherein in the step C, the scheme of the motor system is checked specifically as follows:
c.1, importing power characteristic data of the motor, and solving the number of the power demand data obtained according to the road spectrum data, which is larger than the number of the data matched with the power characteristic of the motor, namely the number of the power demand data which does not meet the road spectrum;
c.2, calculating the proportion of the unsatisfied demand power data in the whole demand power data;
c.3 setting threshold value w0When the specific gravity is not less than w when the road spectrum power requirement is not met0If so, the motor is considered not to meet the requirement;
c.4, setting the percentage threshold of the motor system efficiency higher than 85% as w1；
C.5, when the specific gravity does not meet the road spectrum power requirement is less than the threshold value w0And the ratio of the motor system efficiency higher than 85 percent is more than or equal to the threshold value w1The motor is deemed to meet the requirements.
8. The power matching method based on the actual operation road according to any one of claims 5 to 7, characterized by further comprising the step D of: and verifying the speed following condition of the optimal power matching scheme by combining system simulation software according to the data of mileage, gradient and time and speed, and further checking the feasibility of the optimal power matching scheme.
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| CN113836635A (en) * | 2021-08-31 | 2021-12-24 | 东风商用车有限公司 | Road spectrum automatic identification method based on passive oil mass distribution calculation inflection point |
| CN114093055A (en) * | 2021-11-26 | 2022-02-25 | 海南小鲨鱼智能科技有限公司 | Road spectrum generation method and device, electronic equipment and medium |
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| CN113804454B (en) * | 2021-08-06 | 2024-03-15 | 中汽研汽车检验中心（天津）有限公司 | Road spectrum acquisition and filtering method for dynamic ventilation test of fuel tank assembly |
| CN113836635A (en) * | 2021-08-31 | 2021-12-24 | 东风商用车有限公司 | Road spectrum automatic identification method based on passive oil mass distribution calculation inflection point |
| CN113836635B (en) * | 2021-08-31 | 2023-06-16 | 东风商用车有限公司 | Road spectrum automatic identification method based on passive oil mass distribution calculation inflection point |
| CN114093055A (en) * | 2021-11-26 | 2022-02-25 | 海南小鲨鱼智能科技有限公司 | Road spectrum generation method and device, electronic equipment and medium |
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Application publication date: 20201023 |