CN119840357B - Intelligent tire pressure automatic regulating method for energy-saving driving - Google Patents
Intelligent tire pressure automatic regulating method for energy-saving drivingInfo
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- CN119840357B CN119840357B CN202510324367.7A CN202510324367A CN119840357B CN 119840357 B CN119840357 B CN 119840357B CN 202510324367 A CN202510324367 A CN 202510324367A CN 119840357 B CN119840357 B CN 119840357B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60C—VEHICLE TYRES; TYRE INFLATION; TYRE CHANGING; CONNECTING VALVES TO INFLATABLE ELASTIC BODIES IN GENERAL; DEVICES OR ARRANGEMENTS RELATED TO TYRES
- B60C23/00—Devices for measuring, signalling, controlling, or distributing tyre pressure or temperature, specially adapted for mounting on vehicles; Arrangement of tyre inflating devices on vehicles, e.g. of pumps or of tanks; Tyre cooling arrangements
- B60C23/001—Devices for manually or automatically controlling or distributing tyre pressure whilst the vehicle is moving
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Abstract
本发明提供了一种用于节能驾驶的智能轮胎气压自动调节方法，涉及数据处理技术领域，包括利用设定监测工具实时监测目标轮胎的气压，得到第一气压数据；根据目标轮胎的应用场景与实时使用工况，确定当前目标轮胎的动态胎压标准；将所述第一气压数据与动态轮胎标准进行比较，并当所述目标轮胎的胎压异常时，自动调节胎压。通过利用设定监测工具实时监测目标轮胎的气压，得到第一气压数据；根据目标轮胎的应用场景与实时使用工况，确定当前目标轮胎的动态胎压标准；将所述第一气压数据与动态轮胎标准进行比较，并当所述目标轮胎的胎压异常时自动调节胎压，可实现对轮胎气压的准确智能调节，进而有助于实现节能驾驶。
The present invention provides an intelligent automatic tire pressure adjustment method for energy-saving driving, which relates to the field of data processing technology, including using a set monitoring tool to monitor the air pressure of a target tire in real time to obtain first air pressure data; determining the dynamic tire pressure standard of the current target tire according to the application scenario and real-time usage conditions of the target tire; comparing the first air pressure data with the dynamic tire standard, and automatically adjusting the tire pressure when the tire pressure of the target tire is abnormal. By using a set monitoring tool to monitor the air pressure of a target tire in real time to obtain first air pressure data; determining the dynamic tire pressure standard of the current target tire according to the application scenario and real-time usage conditions of the target tire; comparing the first air pressure data with the dynamic tire standard, and automatically adjusting the tire pressure when the tire pressure of the target tire is abnormal, accurate and intelligent adjustment of the tire pressure can be achieved, thereby contributing to energy-saving driving.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to an intelligent tire pressure automatic adjusting method for energy-saving driving.
Background
Tire pressure is one of the key factors affecting automobile energy efficiency and driving safety. Maintaining proper tire pressure can reduce the friction between the tire and the ground, reduce fuel consumption, and simultaneously contribute to improving driving stability and safety. However, the traditional tire pressure adjusting mode needs to be manually carried out by a driver, so that the operation is complicated, the accuracy and stability of the air pressure are difficult to ensure, and therefore, how to intelligently adjust the tire pressure is beneficial to realizing energy-saving driving becomes one of the centers of gravity of the current study.
Therefore, the invention provides an intelligent tire pressure automatic adjusting method for energy-saving driving.
Disclosure of Invention
The invention provides an intelligent tire pressure automatic regulating method for energy-saving driving, which is used for obtaining first air pressure data by monitoring the air pressure of a target tire in real time by using a set monitoring tool, determining the dynamic tire pressure standard of the current target tire according to the application scene and the real-time use working condition of the target tire, comparing the first air pressure data with the dynamic tire standard, and automatically regulating the tire pressure when the tire pressure of the target tire is abnormal, so that the accurate intelligent regulation of the tire pressure can be realized, and the energy-saving driving is facilitated.
The invention provides an intelligent tire pressure automatic regulating method for energy-saving driving, which comprises the following steps:
Step1, monitoring the air pressure of a target tire in real time by using a set monitoring tool to obtain first air pressure data;
step2, combining the application scene and the actual use condition of the target tire, and determining the real-time dynamic tire pressure standard range of the current target tire;
step3, comparing the first air pressure data with a real-time dynamic tire pressure standard range, and automatically adjusting the tire pressure when the tire pressure of the target tire is abnormal;
Wherein, step 2 includes:
carrying out road surface shooting according to a preset frequency by using a set camera arranged on the front side of the target tire to obtain a road surface image set;
performing key frame extraction and key frame image processing on the pavement image set to obtain a key pavement image;
Analyzing the road condition of the road surface on which the target tire runs in front based on the key road surface image to obtain a road condition evaluation coefficient;
taking key basic information and road condition evaluation coefficients of the current target tire as setting factors to acquire a dynamic tire pressure standard range;
and screening the dynamic tire pressure standard range to obtain an optimal dynamic tire pressure standard range, and outputting the optimal dynamic tire pressure standard range as a real-time dynamic tire pressure standard range of the current target tire.
Preferably, the setting monitoring tool is used for monitoring the air pressure of the target tire in real time to obtain first air pressure data, and the method comprises the following steps:
Determining the number of tools for installing and setting monitoring tools and designated monitoring points according to the basic information of the target tire;
establishing a tire-monitoring tool list for the target tire, wherein the tire-monitoring tool list records the tool use condition of each set monitoring tool;
and installing the set monitoring tool to an appointed monitoring point in the target tire and monitoring in real time to obtain first air pressure data of the target tire.
Preferably, the key basic information includes the type and load range of the vehicle to which the tire belongs, and the type and specification of the tire.
Preferably, the analyzing the road condition of the road surface of the front running of the target tire based on the key road surface image to obtain the road condition evaluation coefficient includes:
Extracting features from the key road surface image by using a pre-established feature extraction model to obtain a first analysis feature;
performing feature screening on the first analysis features by using a set feature selection algorithm to obtain key analysis features;
The key analysis features and the road surface types are used as matching conditions, a first road surface condition graph with feature similarity scores of the reference image features and the key analysis features larger than a set feature similarity threshold is obtained by matching from a preset road surface condition library, and a first road surface condition graph set is obtained by integration;
Acquiring a corresponding road condition evaluation coefficient of each first road condition graph in the first road condition graph set, and calculating to obtain a key evaluation coefficient by combining the feature similarity score;
the calculation formula of the key evaluation coefficient is as follows:
In the formula (I), in the formula (II), Representing as a corresponding key evaluation coefficient of the current target tire; The road condition evaluation coefficient expressed as the i-th first road condition map in the corresponding first road condition map set of the current target tire, wherein i=1, 2,3, N is the total number of the first road surface condition graphs in the first road surface condition graph set; representing feature similarity scores of key analysis features acquired from corresponding key road surface images of the current target tire and reference image features of an ith first road surface condition map; representing as a maximum score obtained from feature similarity scores of key analysis features obtained from a corresponding key road surface image of a current target tire and reference image features of all first road surface condition maps; Representing as a minimum score obtained from feature similarity scores of key analysis features obtained from a corresponding key road surface image of the current target tire and reference image features of all the first road surface condition maps; representing as an average score obtained from feature similarity scores of key analysis features obtained from corresponding key road surface images of the current target tire and reference image features of all the first road surface condition maps;
And taking the key evaluation coefficient as a road condition evaluation coefficient of the road surface to be driven in front of the current target tire.
Preferably, the screening to obtain the optimal dynamic tire pressure standard range from the dynamic tire pressure standard range includes:
acquiring a first tire using a dynamic tire pressure standard which belongs to the current dynamic tire pressure standard range;
screening tires with key basic information consistent with the target tire from the first tires, marking the tires as reference tires, and marking the vehicles corresponding to the reference tires as reference vehicles;
acquiring historical driving condition data of a corresponding reference vehicle when the reference tire is set to be a dynamic tire pressure standard within a current dynamic tire pressure standard range;
Preprocessing the acquired historical driving condition data, inputting the preprocessed historical driving condition data into a pre-established energy-saving evaluation model, and analyzing the energy-saving performance of the current reference vehicle to obtain an energy-saving performance evaluation coefficient;
marking a reference tire with the energy-saving performance evaluation coefficient exceeding a set energy-saving performance threshold value as a reference tire;
When only a single reference tire exists, regarding a dynamic tire pressure standard set when the energy-saving performance evaluation coefficient of the reference tire is highest as a reference tire pressure standard, and marking the corresponding reference tire as a key tire;
when a plurality of reference tires exist, summarizing dynamic tire pressure standards set when the energy-saving performance evaluation coefficients of all the reference tires are the best according to the energy-saving performance evaluation coefficients from large to small to obtain a reference tire pressure standard list;
Selecting a first tire pressure standard in a reference tire pressure standard list as a key tire pressure standard to be output, and marking a reference tire corresponding to the key tire pressure standard as a key tire;
and obtaining set adjustment parameters by analyzing the difference between the key tire and the target tire, adjusting the key tire pressure standard, and then outputting the adjusted key tire pressure standard as an optimal dynamic tire pressure standard range.
Preferably, the setting adjustment parameters are obtained by analyzing the difference between the key tire and the target tire, and the key tire pressure standard is adjusted and then is used as the optimal dynamic tire pressure standard range and output, which comprises the following steps:
sequentially extracting historical wear data of the current key tire and the target tire from a tire use database, and marking the historical wear data as first wear data and second wear data respectively;
Performing wear degree analysis on the acquired first wear data or second wear data by setting wear analysis indexes, and correspondingly obtaining actual wear coefficients of the key tire or the target tire;
calculating to obtain a set adjustment parameter based on actual wear coefficients of the key tire and the target tire;
the calculation formula for setting the adjustment parameters is as follows:
In the formula (I), in the formula (II), Indicated as setting adjustment parameters; the actual wear coefficient expressed as a key tire; Expressed as the actual wear coefficient of the target tire; average value of corresponding road surface evaluation coefficients expressed as the current key tire pressure standard for the key tire; road condition evaluation coefficients expressed as the running road surface of the current target tire; expressed as a disparity compensation coefficient;
and adjusting the key tire pressure standard by adopting the set adjustment parameters to obtain an optimal dynamic tire pressure standard range and outputting the optimal dynamic tire pressure standard range.
Preferably, comparing the first air pressure data with a real-time dynamic tire pressure standard range, and automatically adjusting the tire pressure when the tire pressure of the target tire is abnormal, including:
Comparing the first air pressure data with a real-time dynamic tire pressure standard range, and judging that the tire pressure of the current target tire is normal when the first air pressure data belongs to the real-time dynamic tire pressure standard range;
when the first air pressure data is larger than the tire pressure standard upper limit of the real-time dynamic tire pressure standard range, judging that the tire pressure of the current target tire is abnormal, and acquiring a first tire pressure difference value between the first air pressure data and the tire pressure standard upper limit and a first tire pressure adjusting direction;
If the first tire pressure difference value is not greater than the set dynamic reference difference threshold value, the target tire is adjusted to the tire pressure standard upper limit at one time according to the first tire pressure adjustment direction;
if the first tire pressure difference distance value is larger than the set dynamic reference difference threshold value, calculating one half of the first tire pressure difference distance value as a first adjustment amount, and performing first tire pressure adjustment on the current target tire according to a first tire pressure adjustment direction;
Acquiring a first residual gap value between the adjusted air pressure data of the target tire after the first tire pressure adjustment and the upper limit of the current tire pressure standard;
Dividing the first residual gap value according to a first set dynamic proportion, obtaining a first fine adjustment amount, and then carrying out tire pressure adjustment with the current target tire with a plurality of adjustment amounts of the first fine adjustment amount in combination with a first tire pressure adjustment direction until the tire pressure adjustment is adjusted to be the upper limit of the tire pressure standard;
When the first air pressure data is smaller than the tire pressure standard lower limit of the real-time dynamic tire pressure standard range, judging that the tire pressure of the current target tire is abnormal, and acquiring a second tire pressure difference value between the first air pressure data and the tire pressure standard lower limit and a second tire pressure adjusting direction;
if the second tire pressure difference value is not greater than the set dynamic reference difference threshold value, the target tire is adjusted to the tire pressure standard lower limit at one time according to the second tire pressure adjustment direction;
If the second tire pressure difference value is larger than the set dynamic reference difference threshold value, calculating one half of the second tire pressure difference value as a second adjustment amount, and performing first tire pressure adjustment on the current target tire according to a second tire pressure adjustment direction;
acquiring a second residual gap value between the adjusted air pressure data of the target tire after the first tire pressure adjustment and the lower limit of the current tire pressure standard;
And dividing the second residual gap value according to a second set dynamic proportion, obtaining a second fine adjustment amount, and then carrying out tire pressure adjustment with the current target tire for a plurality of times according to the second tire pressure adjustment direction, wherein the adjustment amount is the second fine adjustment amount, until the tire pressure adjustment is the lower limit of the tire pressure standard.
Compared with the prior art, the application has the following beneficial effects:
The method comprises the steps of obtaining first air pressure data by monitoring the air pressure of a target tire in real time through a set monitoring tool, determining the dynamic tire pressure standard of the current target tire according to the application scene and the real-time use working condition of the target tire, comparing the first air pressure data with the dynamic tire standard, and automatically adjusting the tire pressure when the tire pressure of the target tire is abnormal, so that the accurate and intelligent adjustment of the air pressure of the tire can be realized, and energy-saving driving is facilitated.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
Fig. 1 is a flowchart of an intelligent tire pressure automatic adjustment method for energy-saving driving according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
The embodiment of the invention provides an intelligent tire air pressure automatic adjusting method for energy-saving driving, which is shown in fig. 1 and comprises the following steps:
Step1, monitoring the air pressure of a target tire in real time by using a set monitoring tool to obtain first air pressure data;
step2, combining the application scene and the actual use condition of the target tire, and determining the real-time dynamic tire pressure standard range of the current target tire;
And 3, comparing the first air pressure data with a real-time dynamic tire pressure standard range, and automatically adjusting the tire pressure when the tire pressure of the target tire is abnormal.
In this embodiment, the setting monitoring tool refers to an apparatus for monitoring the air pressure of the target tire in real time, such as a built-in tire pressure monitoring sensor, the first air pressure data refers to the air pressure value of the target tire monitored by the setting monitoring tool in real time, the application scenario refers to the road surface environmental condition used by the target tire, the actual usage condition refers to the historical usage data (such as the historical usage time, the historical usage time length) and the historical maintenance data (such as the historical maintenance times, the historical maintenance content) of the target tire, and the real-time dynamic tire pressure standard range refers to the tire pressure range determined by considering the application scenario and the actual usage condition of the target tire.
The technical scheme has the advantages that the air pressure of the target tire is monitored in real time by using the set monitoring tool to obtain first air pressure data, the dynamic tire pressure standard of the current target tire is determined according to the application scene and the real-time use working condition of the target tire, the first air pressure data is compared with the dynamic tire standard, the tire pressure is automatically regulated when the tire pressure of the target tire is abnormal, accurate and intelligent regulation of the air pressure of the tire can be achieved, and energy-saving driving is facilitated.
The embodiment of the invention provides an intelligent tire pressure automatic regulating method for energy-saving driving, which monitors the air pressure of a target tire in real time by using a set monitoring tool to obtain first air pressure data, and comprises the following steps:
Determining the number of tools for installing and setting monitoring tools and designated monitoring points according to the basic information of the target tire;
establishing a tire-monitoring tool list for the target tire, wherein the tire-monitoring tool list records the tool use condition of each set monitoring tool;
and installing the set monitoring tool to an appointed monitoring point in the target tire and monitoring in real time to obtain first air pressure data of the target tire.
In this embodiment, the basic information of the tire includes the model and load range of the vehicle to which the tire belongs, as well as the tire type (such as radial tire, bias tire, tubeless tire) and specification (including size, tire width, flatness, etc.), the set monitoring tool refers to an apparatus for monitoring the air pressure of the target tire in real time, such as a built-in tire pressure monitoring sensor, the number of tools refers to the number of monitoring tools required to be installed in order to achieve real-time monitoring of the tire air pressure, the number of monitoring tools required to be installed is determined from a predetermined monitoring tool-number table, which is a list of the size range of the tire and the corresponding number of tool installation, the designated monitoring point refers to a specific position of the monitoring tool installed in the tire set in advance, the tire-monitoring tool list refers to a list for recording the relationship between each tire and its corresponding monitoring tool, and the tool use condition of the set monitoring tool, wherein the tool use condition includes, but is not limited to, the installation date, the operating state, maintenance history, etc., the first air pressure data is the real-time monitoring data of the air pressure obtained by the designated monitoring tool installed inside the target tire.
The technical scheme has the beneficial effects that the air pressure of the target tire is monitored in real time by utilizing the set monitoring tool, and the first air pressure data can provide an effective data basis for automatically adjusting the air pressure of the tire subsequently.
The embodiment of the invention provides an intelligent tire pressure automatic regulating method for energy-saving driving, which combines an application scene and actual use working conditions of a target tire to determine a real-time dynamic tire pressure standard range of the current target tire, and comprises the following steps:
carrying out road surface shooting according to a preset frequency by using a set camera arranged on the front side of the target tire to obtain a road surface image set;
performing key frame extraction and key frame image processing on the pavement image set to obtain a key pavement image;
Analyzing the road condition of the road surface on which the target tire runs in front based on the key road surface image to obtain a road condition evaluation coefficient;
taking key basic information and road condition evaluation coefficients of the current target tire as setting factors to acquire a dynamic tire pressure standard range;
and screening the dynamic tire pressure standard range to obtain an optimal dynamic tire pressure standard range, and outputting the optimal dynamic tire pressure standard range as a real-time dynamic tire pressure standard range of the current target tire.
In the embodiment, the setting camera is a high-definition camera installed on the front side of a target tire and used for shooting road conditions about to run in front of the tire, the preset frequency is a time interval for shooting the road by the camera, the road image set is a set of images obtained by shooting the road on the road in front of the target tire according to the preset frequency by the setting camera, the key road image is obtained by extracting key frames from the road image set and then carrying out image processing on the extracted key frames, wherein the key frames are image frames with frame definition which is selected from the road image set and is larger than a set definition threshold, the frame definition is obtained by carrying out weighted average on evaluation values obtained by evaluating definition indexes, wherein the definition indexes comprise gradient mean values, gradient variances and Laplacian variances, the gradient magnitude of each pixel point is calculated by calculating the gradient of the image in the horizontal and vertical directions by utilizing an image gradient operator, the weight which is given to the evaluation values of the definition indexes after evaluation are obtained by carrying out two-two comparison and relative importance score construction by adopting an analysis method according to the gradient magnitude of the whole image, and the preset definition index is set to be a general definition threshold of 0.7.
In the embodiment, the image processing refers to image enhancement and denoising, the road condition evaluation coefficient refers to a quantization index obtained by analyzing the road condition of the road surface running in front of the target tire based on the key road surface image, the dynamic tire pressure standard range refers to a tire pressure range determined according to key basic information of the current target tire and the road condition evaluation coefficient, the optimal dynamic tire pressure standard range refers to an optimal standard range screened from the dynamic tire pressure standard ranges, and the real-time dynamic tire pressure standard range refers to a tire pressure range which is finally determined and used by the current target tire.
The technical scheme has the advantages that the key frames are screened by analyzing the definition of the concentrated images of the road surface images, the key road surface images are obtained after the key frames are processed, the road condition evaluation coefficient is obtained by analyzing the road condition of the road surface running in front of the target tire based on the key road surface images, and then the real-time dynamic tire pressure standard range is effectively determined.
The embodiment of the invention provides an intelligent tire air pressure automatic regulating method for energy-saving driving, which is used for analyzing the road condition of a road surface running in front of a target tire based on the key road surface image to obtain a road condition evaluation coefficient, and comprises the following steps:
Extracting features from the key road surface image by using a pre-established feature extraction model to obtain a first analysis feature;
performing feature screening on the first analysis features by using a set feature selection algorithm to obtain key analysis features;
The key analysis features and the road surface types are used as matching conditions, a first road surface condition graph with feature similarity scores of the reference image features and the key analysis features larger than a set feature similarity threshold is obtained by matching from a preset road surface condition library, and a first road surface condition graph set is obtained by integration;
Acquiring a corresponding road condition evaluation coefficient of each first road condition graph in the first road condition graph set, and calculating to obtain a key evaluation coefficient by combining the feature similarity score;
the calculation formula of the key evaluation coefficient is as follows:
In the formula (I), in the formula (II), Representing as a corresponding key evaluation coefficient of the current target tire; The road condition evaluation coefficient expressed as the i-th first road condition map in the corresponding first road condition map set of the current target tire, wherein i=1, 2,3, N is the total number of the first road surface condition graphs in the first road surface condition graph set; representing feature similarity scores of key analysis features acquired from corresponding key road surface images of the current target tire and reference image features of an ith first road surface condition map; representing as a maximum score obtained from feature similarity scores of key analysis features obtained from a corresponding key road surface image of a current target tire and reference image features of all first road surface condition maps; Representing as a minimum score obtained from feature similarity scores of key analysis features obtained from a corresponding key road surface image of the current target tire and reference image features of all the first road surface condition maps; representing as an average score obtained from feature similarity scores of key analysis features obtained from corresponding key road surface images of the current target tire and reference image features of all the first road surface condition maps;
And taking the key evaluation coefficient as a road condition evaluation coefficient of the road surface to be driven in front of the current target tire.
In this embodiment, the feature extraction model is a model for extracting features from an image, and is obtained by collecting a large amount of image data including different road conditions (such as dry, slippery, cracked, pitted, etc.), training a neural network, the first analysis features are preliminary feature sets extracted from the key road images by using the feature extraction model, such as pixel values and color distribution of the images, a feature selection algorithm is set for screening out key features from the preliminary feature sets, and a filtering method (such as a variance selection method and a correlation coefficient selection method) is generally adopted, and the key analysis features are feature sets which are screened out from the first analysis features and have higher importance on road analysis, including road surface leveling features, crack features, slippery degree features, colors, texture features, etc.
In this embodiment, the preset road condition library is a database including a plurality of road condition images, corresponding reference image features and road condition evaluation coefficients, the reference image features are corresponding feature representations of each road condition image in the preset road condition library, feature similarity scores are used for measuring similarity between two feature sets and are calculated by using a cosine similarity algorithm, a set feature similarity threshold is predetermined and is generally 0.75, a first road condition map is a road condition image with similarity to a key analysis feature exceeding the set feature similarity threshold, and a first road condition map is a set of all road condition images with similarity to the key analysis feature exceeding the set feature similarity threshold.
The technical scheme has the beneficial effects that the road condition analysis of the road surface running in front of the target tire is realized by utilizing advanced image processing and machine learning technologies, the road condition evaluation coefficient is obtained, and a data basis is provided for the subsequent tire pressure adjustment.
The embodiment of the invention provides an intelligent tire pressure automatic regulating method for energy-saving driving, which screens an optimal dynamic tire pressure standard range from the dynamic tire pressure standard range, and comprises the following steps:
acquiring a first tire using a dynamic tire pressure standard which belongs to the current dynamic tire pressure standard range;
screening tires with key basic information consistent with the target tire from the first tires, marking the tires as reference tires, and marking the vehicles corresponding to the reference tires as reference vehicles;
acquiring historical driving condition data of a corresponding reference vehicle when the reference tire is set to be a dynamic tire pressure standard within a current dynamic tire pressure standard range;
Preprocessing the acquired historical driving condition data, inputting the preprocessed historical driving condition data into a pre-established energy-saving evaluation model, and analyzing the energy-saving performance of the current reference vehicle to obtain an energy-saving performance evaluation coefficient;
marking a reference tire with the energy-saving performance evaluation coefficient exceeding a set energy-saving performance threshold value as a reference tire;
When only a single reference tire exists, regarding a dynamic tire pressure standard set when the energy-saving performance evaluation coefficient of the reference tire is highest as a reference tire pressure standard, and marking the corresponding reference tire as a key tire;
when a plurality of reference tires exist, summarizing dynamic tire pressure standards set when the energy-saving performance evaluation coefficients of all the reference tires are the best according to the energy-saving performance evaluation coefficients from large to small to obtain a reference tire pressure standard list;
Selecting a first tire pressure standard in a reference tire pressure standard list as a key tire pressure standard to be output, and marking a reference tire corresponding to the key tire pressure standard as a key tire;
and obtaining set adjustment parameters by analyzing the difference between the key tire and the target tire, adjusting the key tire pressure standard, and then outputting the adjusted key tire pressure standard as an optimal dynamic tire pressure standard range.
In this embodiment, the first tire refers to a tire in which the dynamic tire pressure is set within a current dynamic tire pressure standard range, wherein the dynamic tire pressure standard range refers to a range including a plurality of different dynamic tire pressure values, the reference tire refers to a tire selected from the first tire, the key basic information of which is consistent with that of the target tire, the reference vehicle refers to a vehicle on which the reference tire is mounted, and the historical driving condition data refers to driving data recorded by the reference vehicle when the reference tire is mounted and set to a specific dynamic tire pressure that belongs to the current dynamic tire pressure standard range, including driving mileage, fuel consumption, speed change, acceleration, and the like.
In the embodiment, the energy-saving evaluation model is a model for evaluating the energy-saving performance of the tire according to the historical driving condition data, which is obtained by collecting a large number of historical driving condition data of a reference vehicle under different dynamic tire pressure standards, preprocessing the data, extracting features (such as average fuel consumption, driving speed distribution, acceleration standard deviation and the like) capable of reflecting the energy-saving performance of the tire, training the neural network by using the extracted features and the processed data as training data, wherein the energy-saving performance evaluation coefficient is a numerical value outputted by the energy-saving evaluation model and used for representing the energy-saving performance of the tire under specific dynamic tire pressure, and the range of the numerical value isThe energy-saving performance threshold value is preset and is generally 0.7, the reference tire refers to a reference tire with the energy-saving performance evaluation coefficient exceeding the energy-saving performance threshold value, the reference tire pressure standard refers to a dynamic tire pressure value set by the reference tire when the energy-saving performance evaluation coefficient is highest, the reference tire pressure standard list is a list obtained by sorting the reference tire pressure standards of all the reference tires according to the energy-saving performance evaluation coefficient from large to small, the key tire refers to a tire with the dynamic tire pressure selected as the key tire pressure standard, namely the tire with the best energy-saving performance, and the adjustment parameter is set for adjusting the key tire pressure standard.
The technical scheme has the beneficial effects that the key tire pressure standard is screened out from the dynamic tire pressure standard range, and the key tire pressure standard is adjusted by setting the adjusting parameter, so that the more accurate optimal dynamic tire pressure standard range is obtained, accurate tire pressure adjustment can be realized, and the energy-saving performance of the vehicle is improved.
The embodiment of the invention provides an intelligent tire pressure automatic regulating method for energy-saving driving, which is used for obtaining set regulating parameters by analyzing the difference between a key tire and a target tire, regulating the key tire pressure standard and then outputting the regulated key tire pressure standard as an optimal dynamic tire pressure standard range, and comprises the following steps:
sequentially extracting historical wear data of the current key tire and the target tire from a tire use database, and marking the historical wear data as first wear data and second wear data respectively;
Performing wear degree analysis on the acquired first wear data or second wear data by setting wear analysis indexes, and correspondingly obtaining actual wear coefficients of the key tire or the target tire;
calculating to obtain a set adjustment parameter based on actual wear coefficients of the key tire and the target tire;
the calculation formula for setting the adjustment parameters is as follows:
In the formula (I), in the formula (II), Indicated as setting adjustment parameters; the actual wear coefficient expressed as a key tire; Expressed as the actual wear coefficient of the target tire; average value of corresponding road surface evaluation coefficients expressed as the current key tire pressure standard for the key tire; road condition evaluation coefficients expressed as the running road surface of the current target tire; expressed as a disparity compensation coefficient;
and adjusting the key tire pressure standard by adopting the set adjustment parameters to obtain an optimal dynamic tire pressure standard range and outputting the optimal dynamic tire pressure standard range.
In this embodiment, the tire usage database refers to a database storing a large amount of tire usage data including the model, specification, date of manufacture, installation vehicle, mileage, wear condition, maintenance record, etc. of tires, the historical wear data refers to wear records of tires including the degree of wear, aging condition, number of cracks, etc. of tires, the first wear data refers to historical wear data of key tires, the second wear data refers to historical wear data of target tires, and the set wear analysis index refers to quantization criteria for evaluating the degree of wear of tires including the depth, width, and uniformity of wear of tires.
In this embodiment, the actual wear factor is obtained by weighted average calculation of wear index values obtained by wear evaluation based on historical wear data using a set wear analysis index, the calculation formula isIn which, in the process,Expressed as actual wear coefficient; A corresponding wear indicator value denoted b-th set wear analysis indicator, wherein b = 1,2,3; The weight given to the wear-level index is obtained by solving a matrix constructed by comparing the set wear-level index by the hierarchical analysis method with the relative importance score.
In the embodiment, the set adjustment parameter is calculated based on factors such as actual wear coefficients of the key tire and the target tire and a road surface evaluation coefficient, and is used for adjusting the key tire pressure standard to obtain a value of an optimal dynamic tire pressure standard range, the difference compensation coefficient is obtained by multiplying a preset data error compensation value by an average use duration of the key tire and the target tire, wherein the preset data error compensation value is obtained by calculating data acquisition deviations of all loss data acquisition tools in a preset time period and then averaging the data acquisition deviations, the loss data acquisition tools are used for acquiring tire wear data, such as sensors, the preset time period is a time period which is preset and can capture stable data acquisition deviations of the loss data acquisition tools, such as one month, and the optimal dynamic tire pressure standard range is a tire pressure range which is obtained by adjusting the key tire pressure standard by adopting the set adjustment parameter and can enable the tire pressure to achieve optimal tire pressure performance.
In this embodiment, for example, the critical tire pressure standard for the presence of the target tire 1 isCurrently, the adjustment parameters are set asThe optimal dynamic tire pressure standard range isIn the formula, e is expressed as a constant and has a value of 2.7.
The technical scheme has the beneficial effects that the set adjustment parameters are obtained by analyzing the dissimilarity between the key tire and the target tire, the key tire pressure standard is adjusted to obtain the optimal dynamic tire pressure standard range, accurate tire pressure adjustment can be realized, and the energy-saving performance of the vehicle is improved.
The embodiment of the invention provides an intelligent tire pressure automatic regulating method for energy-saving driving, which compares first air pressure data with a real-time dynamic tire pressure standard range, automatically regulates the tire pressure when the tire pressure of a target tire is abnormal, and comprises the following steps:
Comparing the first air pressure data with a real-time dynamic tire pressure standard range, and judging that the tire pressure of the current target tire is normal when the first air pressure data belongs to the real-time dynamic tire pressure standard range;
when the first air pressure data is larger than the tire pressure standard upper limit of the real-time dynamic tire pressure standard range, judging that the tire pressure of the current target tire is abnormal, and acquiring a first tire pressure difference value between the first air pressure data and the tire pressure standard upper limit and a first tire pressure adjusting direction;
If the first tire pressure difference value is not greater than the set dynamic reference difference threshold value, the target tire is adjusted to the tire pressure standard upper limit at one time according to the first tire pressure adjustment direction;
if the first tire pressure difference distance value is larger than the set dynamic reference difference threshold value, calculating one half of the first tire pressure difference distance value as a first adjustment amount, and performing first tire pressure adjustment on the current target tire according to a first tire pressure adjustment direction;
Acquiring a first residual gap value between the adjusted air pressure data of the target tire after the first tire pressure adjustment and the upper limit of the current tire pressure standard;
Dividing the first residual gap value according to a first set dynamic proportion, obtaining a first fine adjustment amount, and then carrying out tire pressure adjustment with the current target tire with a plurality of adjustment amounts of the first fine adjustment amount in combination with a first tire pressure adjustment direction until the tire pressure adjustment is adjusted to be the upper limit of the tire pressure standard;
When the first air pressure data is smaller than the tire pressure standard lower limit of the real-time dynamic tire pressure standard range, judging that the tire pressure of the current target tire is abnormal, and acquiring a second tire pressure difference value between the first air pressure data and the tire pressure standard lower limit and a second tire pressure adjusting direction;
if the second tire pressure difference value is not greater than the set dynamic reference difference threshold value, the target tire is adjusted to the tire pressure standard lower limit at one time according to the second tire pressure adjustment direction;
If the second tire pressure difference value is larger than the set dynamic reference difference threshold value, calculating one half of the second tire pressure difference value as a second adjustment amount, and performing first tire pressure adjustment on the current target tire according to a second tire pressure adjustment direction;
acquiring a second residual gap value between the adjusted air pressure data of the target tire after the first tire pressure adjustment and the lower limit of the current tire pressure standard;
And dividing the second residual gap value according to a second set dynamic proportion, obtaining a second fine adjustment amount, and then carrying out tire pressure adjustment with the current target tire for a plurality of times according to the second tire pressure adjustment direction, wherein the adjustment amount is the second fine adjustment amount, until the tire pressure adjustment is the lower limit of the tire pressure standard.
In the embodiment, the upper tire pressure standard limit refers to the maximum tire pressure in the real-time dynamic tire pressure standard range, the lower tire pressure standard limit refers to the minimum tire pressure in the real-time dynamic tire pressure standard range, the first tire pressure difference value refers to the difference between the tire pressure of the target tire and the upper tire pressure standard limit when the tire pressure of the target tire (i.e., the first air pressure data) is higher than the upper tire pressure standard limit, the first tire pressure adjustment direction refers to the reduction of the tire pressure, the dynamic reference difference threshold is preset and is generally set to be one fifth of the absolute difference between the upper tire pressure standard limit and the lower tire pressure standard limit of the current real-time dynamic tire pressure standard range, the first adjustment amount is obtained by taking one half of the first tire pressure difference value when the first tire pressure difference value is larger than the dynamic reference difference threshold, the first residual difference value refers to the difference value between the tire pressure of the target tire and the upper tire pressure standard limit after the first adjustment by the first adjustment amount, and the first set dynamic ratio refers to the predetermined ratio for subdividing the first residual difference value, which is expressed as a formulaIn the formula (I), in the formula (II),Represented as a first set dynamic ratio; Represented as a first residual gap value; The first fine adjustment amount refers to the amount of fine adjustment each time obtained by dividing the first residual gap value according to the first set dynamic proportion.
In this embodiment, the second air pressure difference value is the difference between the air pressure of the target tire and the air pressure standard lower limit when the air pressure of the target tire (i.e., the first air pressure data) is lower than the air pressure standard lower limit, the second air pressure adjustment direction is to increase the air pressure, the second adjustment amount is obtained by taking one half of the second air pressure difference value when the second air pressure difference value is greater than the set dynamic reference difference threshold, the second residual difference value is the difference value existing between the air pressure of the target tire and the air pressure standard lower limit after the first air pressure adjustment by the second adjustment amount, the second set dynamic ratio is the predetermined ratio for subdividing the second residual difference value, and the formula is thatIn the formula (I), in the formula (II),2 Is denoted as a second set dynamic ratio; Represented as a second residual gap value; the second fine adjustment amount is the amount of fine adjustment each time obtained by dividing the second residual gap value according to the second set dynamic proportion.
The technical scheme has the beneficial effects that the first air pressure data is compared with the real-time dynamic tire pressure standard range, and when the tire pressure of the target tire is abnormal, the tire pressure is automatically regulated, so that the accurate regulation of the tire pressure can be realized, and the energy-saving performance of the vehicle is effectively improved.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (7)
1. An intelligent tire pressure automatic adjustment method for energy-saving driving, comprising:
Step1, monitoring the air pressure of a target tire in real time by using a set monitoring tool to obtain first air pressure data;
step2, combining the application scene and the actual use condition of the target tire, and determining the real-time dynamic tire pressure standard range of the current target tire;
step3, comparing the first air pressure data with a real-time dynamic tire pressure standard range, and automatically adjusting the tire pressure when the tire pressure of the target tire is abnormal;
wherein, step 2 includes:
Obtaining key analysis features based on the key road surface images;
The key analysis features and the road surface types are used as matching conditions, a first road surface condition graph with feature similarity scores of the reference image features and the key analysis features larger than a set feature similarity threshold is obtained by matching from a preset road surface condition library, and a first road surface condition graph set is obtained by integration;
Acquiring a corresponding road condition evaluation coefficient of each first road condition graph in the first road condition graph set, and calculating to obtain a key evaluation coefficient by combining the feature similarity score;
;
In the formula, Representing as a corresponding key evaluation coefficient of the current target tire; The road condition evaluation coefficient expressed as the i-th first road condition map in the corresponding first road condition map set of the current target tire, wherein i=1, 2,3, N is the total number of the first road surface condition graphs in the first road surface condition graph set; representing feature similarity scores of key analysis features acquired from corresponding key road surface images of the current target tire and reference image features of an ith first road surface condition map; representing as a maximum score obtained from feature similarity scores of key analysis features obtained from a corresponding key road surface image of a current target tire and reference image features of all first road surface condition maps; Representing as a minimum score obtained from feature similarity scores of key analysis features obtained from a corresponding key road surface image of the current target tire and reference image features of all the first road surface condition maps; representing as an average score obtained from feature similarity scores of key analysis features obtained from corresponding key road surface images of the current target tire and reference image features of all the first road surface condition maps;
And taking the key evaluation coefficient as a road condition evaluation coefficient of the road surface to be driven in front of the current target tire.
2. The intelligent tire pressure automatic adjustment method for energy-saving driving according to claim 1, wherein step 2 further comprises:
carrying out road surface shooting according to a preset frequency by using a set camera arranged on the front side of the target tire to obtain a road surface image set;
performing key frame extraction and key frame image processing on the pavement image set to obtain a key pavement image;
Extracting features from the key road surface image by using a pre-established feature extraction model to obtain a first analysis feature;
performing feature screening on the first analysis features by using a set feature selection algorithm to obtain key analysis features;
taking key basic information and road condition evaluation coefficients of the current target tire as setting factors to acquire a dynamic tire pressure standard range;
and screening the dynamic tire pressure standard range to obtain an optimal dynamic tire pressure standard range, and outputting the optimal dynamic tire pressure standard range as a real-time dynamic tire pressure standard range of the current target tire.
3. The method for automatically adjusting the air pressure of an intelligent tire for energy-saving driving according to claim 1, wherein the air pressure of a target tire is monitored in real time by using a set monitoring tool to obtain first air pressure data, comprising:
Determining the number of tools for installing and setting monitoring tools and designated monitoring points according to the basic information of the target tire;
establishing a tire-monitoring tool list for the target tire, wherein the tire-monitoring tool list records the tool use condition of each set monitoring tool;
and installing the set monitoring tool to an appointed monitoring point in the target tire and monitoring in real time to obtain first air pressure data of the target tire.
4. The intelligent tire pressure automatic adjustment method for energy-saving driving according to claim 1, wherein the key basic information comprises the type and load range of the vehicle to which the tire belongs, and the type and specification of the tire.
5. The method for automatically adjusting the air pressure of an intelligent tire for energy-saving driving according to claim 2, wherein the step of screening the optimal dynamic tire pressure standard range from the dynamic tire pressure standard ranges comprises the steps of:
acquiring a first tire using a dynamic tire pressure standard which belongs to the current dynamic tire pressure standard range;
screening tires with key basic information consistent with the target tire from the first tires, marking the tires as reference tires, and marking the vehicles corresponding to the reference tires as reference vehicles;
acquiring historical driving condition data of a corresponding reference vehicle when the reference tire is set to be a dynamic tire pressure standard within a current dynamic tire pressure standard range;
Preprocessing the acquired historical driving condition data, inputting the preprocessed historical driving condition data into a pre-established energy-saving evaluation model, and analyzing the energy-saving performance of the current reference vehicle to obtain an energy-saving performance evaluation coefficient;
marking a reference tire with the energy-saving performance evaluation coefficient exceeding a set energy-saving performance threshold value as a reference tire;
When only a single reference tire exists, regarding a dynamic tire pressure standard set when the energy-saving performance evaluation coefficient of the reference tire is highest as a reference tire pressure standard, and marking the corresponding reference tire as a key tire;
when a plurality of reference tires exist, summarizing dynamic tire pressure standards set when the energy-saving performance evaluation coefficients of all the reference tires are the best according to the energy-saving performance evaluation coefficients from large to small to obtain a reference tire pressure standard list;
Selecting a first tire pressure standard in a reference tire pressure standard list as a key tire pressure standard to be output, and marking a reference tire corresponding to the key tire pressure standard as a key tire;
and obtaining set adjustment parameters by analyzing the difference between the key tire and the target tire, adjusting the key tire pressure standard, and then outputting the adjusted key tire pressure standard as an optimal dynamic tire pressure standard range.
6. The method for automatically adjusting the air pressure of an intelligent tire for energy-saving driving according to claim 5, wherein the set adjustment parameters are obtained by analyzing the difference between the key tire and the target tire, the key tire pressure standard is adjusted and then used as the optimal dynamic tire pressure standard range, and the method comprises the following steps:
sequentially extracting historical wear data of the current key tire and the target tire from a tire use database, and marking the historical wear data as first wear data and second wear data respectively;
Performing wear degree analysis on the acquired first wear data or second wear data by setting wear analysis indexes, and correspondingly obtaining actual wear coefficients of the key tire or the target tire;
calculating to obtain a set adjustment parameter based on actual wear coefficients of the key tire and the target tire;
the calculation formula for setting the adjustment parameters is as follows:
In the formula (I), in the formula (II), Indicated as setting adjustment parameters; the actual wear coefficient expressed as a key tire; Expressed as the actual wear coefficient of the target tire; average value of corresponding road surface evaluation coefficients expressed as the current key tire pressure standard for the key tire; road condition evaluation coefficients expressed as the running road surface of the current target tire; expressed as a disparity compensation coefficient;
and adjusting the key tire pressure standard by adopting the set adjustment parameters to obtain an optimal dynamic tire pressure standard range and outputting the optimal dynamic tire pressure standard range.
7. The intelligent tire air pressure automatic adjustment method for energy-saving driving according to claim 1, wherein comparing the first air pressure data with a real-time dynamic tire pressure standard range, and automatically adjusting the tire pressure when the tire pressure of the target tire is abnormal, comprises:
Comparing the first air pressure data with a real-time dynamic tire pressure standard range, and judging that the tire pressure of the current target tire is normal when the first air pressure data belongs to the real-time dynamic tire pressure standard range;
when the first air pressure data is larger than the tire pressure standard upper limit of the real-time dynamic tire pressure standard range, judging that the tire pressure of the current target tire is abnormal, and acquiring a first tire pressure difference value between the first air pressure data and the tire pressure standard upper limit and a first tire pressure adjusting direction;
If the first tire pressure difference value is not greater than the set dynamic reference difference threshold value, the target tire is adjusted to the tire pressure standard upper limit at one time according to the first tire pressure adjustment direction;
if the first tire pressure difference distance value is larger than the set dynamic reference difference threshold value, calculating one half of the first tire pressure difference distance value as a first adjustment amount, and performing first tire pressure adjustment on the current target tire according to a first tire pressure adjustment direction;
Acquiring a first residual gap value between the adjusted air pressure data of the target tire after the first tire pressure adjustment and the upper limit of the current tire pressure standard;
Dividing the first residual gap value according to a first set dynamic proportion, obtaining a first fine adjustment amount, and then carrying out tire pressure adjustment with the current target tire with a plurality of adjustment amounts of the first fine adjustment amount in combination with a first tire pressure adjustment direction until the tire pressure adjustment is adjusted to be the upper limit of the tire pressure standard;
When the first air pressure data is smaller than the tire pressure standard lower limit of the real-time dynamic tire pressure standard range, judging that the tire pressure of the current target tire is abnormal, and acquiring a second tire pressure difference value between the first air pressure data and the tire pressure standard lower limit and a second tire pressure adjusting direction;
if the second tire pressure difference value is not greater than the set dynamic reference difference threshold value, the target tire is adjusted to the tire pressure standard lower limit at one time according to the second tire pressure adjustment direction;
If the second tire pressure difference value is larger than the set dynamic reference difference threshold value, calculating one half of the second tire pressure difference value as a second adjustment amount, and performing first tire pressure adjustment on the current target tire according to a second tire pressure adjustment direction;
acquiring a second residual gap value between the adjusted air pressure data of the target tire after the first tire pressure adjustment and the lower limit of the current tire pressure standard;
And dividing the second residual gap value according to a second set dynamic proportion, obtaining a second fine adjustment amount, and then carrying out tire pressure adjustment with the current target tire for a plurality of times according to the second tire pressure adjustment direction, wherein the adjustment amount is the second fine adjustment amount, until the tire pressure adjustment is the lower limit of the tire pressure standard.
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| CN116787968A (en) * | 2023-06-29 | 2023-09-22 | 重庆赛力斯新能源汽车设计院有限公司 | Tire pressure monitoring method and device, electronic equipment and readable storage medium |
| CN118478619A (en) * | 2024-04-30 | 2024-08-13 | 广州祥行电子科技有限公司 | Automobile tire pressure control method and system |
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| JP2850608B2 (en) * | 1991-11-28 | 1999-01-27 | 日産自動車株式会社 | Roadway detection device for vehicles |
| US8108119B2 (en) * | 2006-04-21 | 2012-01-31 | Sri International | Apparatus and method for object detection and tracking and roadway awareness using stereo cameras |
| JP5122790B2 (en) * | 2006-11-06 | 2013-01-16 | 株式会社ブリヂストン | Vehicle running body performance prediction method, apparatus and program |
| JP2011131688A (en) * | 2009-12-24 | 2011-07-07 | Kyocera Corp | Module for detecting road surface condition and module for detecting tire air pressure including the same |
| DE102012112724A1 (en) * | 2012-12-20 | 2014-06-26 | Continental Teves Ag & Co. Ohg | Method for determining a road condition from environmental sensor data |
| US12384207B2 (en) * | 2020-01-24 | 2025-08-12 | Toyota Motor Engineering & Manufacturing North America, Inc. | Central tire inflation system |
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