CN117552854A - Method and device for predicting icing degree of crankcase ventilation system of vehicle - Google Patents
Method and device for predicting icing degree of crankcase ventilation system of vehicle Download PDFInfo
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- CN117552854A CN117552854A CN202210917668.7A CN202210917668A CN117552854A CN 117552854 A CN117552854 A CN 117552854A CN 202210917668 A CN202210917668 A CN 202210917668A CN 117552854 A CN117552854 A CN 117552854A
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F01—MACHINES OR ENGINES IN GENERAL; ENGINE PLANTS IN GENERAL; STEAM ENGINES
- F01M—LUBRICATING OF MACHINES OR ENGINES IN GENERAL; LUBRICATING INTERNAL COMBUSTION ENGINES; CRANKCASE VENTILATING
- F01M13/00—Crankcase ventilating or breathing
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Abstract
The embodiment of the invention provides a method and a device for predicting the icing degree of a crankcase ventilation system of a vehicle. The first operating condition data includes an ambient temperature, an ambient humidity, a vehicle speed, and a crankcase blow-by. And the user knows the icing degree in the crankcase ventilation system according to the prediction result, so that corresponding treatment measures are taken to avoid the engine fault caused by serious icing in the crankcase ventilation system.
Description
Technical Field
The invention relates to the technical field of vehicle-mounted equipment, in particular to a method and a device for predicting icing degree of a vehicle crankcase ventilation system.
Background
According to related regulations, in order to meet increasingly strict automobile exhaust emission regulations, a crankcase ventilation system is generally provided for a gasoline engine so as to reintroduce fuel vapor which is not completely combusted in a crankcase into an intake manifold, thereby achieving the purposes of reducing the emission of pollutants in the crankcase and improving the utilization rate of gasoline.
In cold winter areas, such as northeast and northwest of China, the temperature is often lower than minus 30 ℃, at this time, hot fuel vapor coming out of the crankcase flows in the crankcase ventilation pipe and accumulates at the junction of the air filter intake pipe in operation, especially in full-load working conditions, and when cold air in the air filter intake pipe encounters the hot vapor coming from the crankcase, the junction of the crankcase ventilation pipe and the air filter intake pipe is easily frozen, thereby blocking the crankcase ventilation pipe. If the ventilation pipe of the crankcase is blocked, the fuel vapor in the crankcase can not be discharged in time, and the pressure in the crankcase can be too high for a long time, so that oil seals leak oil before and after an engine, and even the oil seals fall off to damage the engine when serious.
Disclosure of Invention
In view of the foregoing, embodiments of the present invention are directed to providing a method for predicting the icing level of a crankcase ventilation system of a vehicle, and a corresponding apparatus, vehicle, and storage medium for predicting the icing level of a crankcase ventilation system of a vehicle, which overcome or at least partially solve the foregoing problems.
In order to solve the above problems, in one aspect, an embodiment of the present invention discloses a method for predicting icing degree of a crankcase ventilation system of a vehicle, the method comprising:
when a vehicle is in a preset working condition, first working condition data of the vehicle operation are collected, and first vehicle operation time corresponding to the first working condition data is determined, wherein the first working condition data comprise ambient temperature, ambient humidity, vehicle speed and crankcase ventilation;
inputting the first working condition data and the first vehicle running time into a preset crankcase ventilation system icing prediction model, and obtaining a prediction result according to the crankcase ventilation system icing prediction model, wherein the prediction result is used for representing the icing degree in the crankcase ventilation system; the method comprises the steps that a crankcase ventilation system icing prediction model is trained by adopting a neural network model, and the crankcase ventilation system icing prediction model is provided with a plurality of mapping relations between vehicle working condition data and the icing degree of a crankcase ventilation system of a vehicle;
and executing preset operation according to the prediction result.
Optionally, the inputting the first working condition data and the first vehicle running time into a preset crankcase ventilation system icing prediction model, and obtaining a prediction result according to the crankcase ventilation system icing prediction model includes:
classifying the first working condition data of the vehicle in the first vehicle running time to obtain target working condition data of a plurality of categories, wherein the vehicle speed and the crankcase gas channeling are the same in the target working condition data of each category;
counting target working condition time corresponding to the target working condition data;
and inputting the target working condition data and the corresponding target working condition time into a preset icing prediction model of the crankcase ventilation system, and obtaining a prediction result.
Optionally, the inputting the target working condition data and the target working condition time into a preset icing prediction model of the crankcase ventilation system to obtain a prediction result includes:
inputting a plurality of target working condition data and a plurality of corresponding target working condition times into a preset crankcase ventilation system icing prediction model to obtain a plurality of target icing data corresponding to the target working condition data respectively;
accumulating and summing a plurality of target icing data to obtain integral icing data;
and determining the whole icing data as the prediction result.
Optionally, the vehicle is provided with an air filter and a supercharger, and before collecting the first working condition data of the vehicle operation, the method further includes:
acquiring the speed of a vehicle;
when the vehicle speed is greater than a preset vehicle speed, starting the supercharger;
after the supercharger is started, acquiring first air pressure of the air filter, second air pressure of a crankcase of a vehicle and third air pressure of an intake manifold;
and if the first air pressure is smaller than the second air pressure and the second air pressure is smaller than the third air pressure, the air in the crankcase is mixed with the air in the air filter through the pipeline, and the vehicle is judged to be in a preset working condition.
Optionally, the training the preset crankcase ventilation system icing model includes:
acquiring training data of a vehicle, wherein the training data comprises second working condition data of the vehicle under a preset working condition and second vehicle running time corresponding to the second working condition data, the second working condition data comprises environment temperature, environment humidity, vehicle speed and crankcase blow-by amount, and the preset working condition comprises environment temperature in a preset temperature interval, environment humidity in a preset humidity interval and vehicle speed in a preset vehicle speed interval;
acquiring actual icing data in a crankcase ventilation system corresponding to the second working condition data;
and training a crankcase ventilation system icing prediction model according to the second working condition data and the actual icing data in the corresponding crankcase ventilation system.
Optionally, the performing a preset operation according to the prediction result includes:
outputting prompt information according to the prediction result;
and/or performing a de-icing function within the crankcase ventilation system based on the prediction.
Optionally, the prediction result has a value for characterizing the icing degree in the crankcase ventilation system, and the outputting, according to the prediction result, a prompt message includes:
if the icing degree value is smaller than the first icing threshold, not outputting prompt information;
reminding a user to adjust the running condition of the vehicle if the icing degree value is between the first icing threshold and the second icing threshold, wherein the first icing threshold is smaller than the second icing threshold;
and if the icing degree value is larger than the second icing threshold, reminding a user to pay attention to the parking information, and executing the deicing function in the crankcase ventilation system of the vehicle.
In another aspect, an embodiment of the present invention discloses a device for predicting icing level of a crankcase ventilation system of a vehicle, including:
the data acquisition module is used for acquiring first working condition data of vehicle operation when the vehicle is in a preset working condition, and determining first vehicle operation time corresponding to the first working condition data, wherein the first working condition data comprises ambient temperature, ambient humidity, vehicle speed and crankcase blow-by;
the data processing module is used for inputting the first working condition data and the first vehicle running time into a preset crankcase ventilation system icing prediction model, obtaining a prediction result according to the crankcase ventilation system icing prediction model, and the prediction result is used for representing the icing degree in the crankcase ventilation system; the method comprises the steps that a crankcase ventilation system icing prediction model is trained by adopting a neural network model, and the crankcase ventilation system icing prediction model is provided with a plurality of mapping relations between vehicle working condition data and the icing degree of a crankcase ventilation system of a vehicle;
and the prediction result execution module is used for executing preset operation according to the prediction result.
Optionally, the data processing module includes:
the working condition data classification sub-module is used for classifying the first working condition data of the vehicle in the first vehicle running time to obtain target working condition data of a plurality of categories, wherein the vehicle speed and the crankcase gas channeling are the same in the target working condition data of each category;
the working condition operation time statistics sub-module is used for counting target working condition time corresponding to the target working condition data;
the working condition data processing sub-module is used for inputting a plurality of target working condition data and a plurality of corresponding target working condition time into a preset icing prediction model of the crankcase ventilation system, and obtaining a prediction result.
Optionally, the working condition data processing submodule includes:
the target icing data acquisition unit is used for inputting a plurality of target working condition data and a plurality of corresponding target working condition time into a preset crankcase ventilation system icing prediction model to obtain a plurality of target icing data corresponding to the target working condition data respectively;
the whole icing data acquisition unit is used for carrying out accumulated summation on a plurality of target icing data to obtain whole icing data;
and the prediction result confirming unit is used for confirming that the whole icing data is the prediction result.
Optionally, the vehicle is provided with an air filter and a supercharger, and before collecting first working condition data of vehicle operation, the device further includes:
the vehicle speed acquisition module is used for acquiring the vehicle speed of the vehicle;
the supercharger control module is used for starting the supercharger when the vehicle speed is greater than a preset vehicle speed;
the air pressure acquisition module is used for acquiring the first air pressure of the air filter, the second air pressure of the crankcase of the vehicle and the third air pressure of the air inlet manifold after the supercharger is started;
and the vehicle operation condition judging module is used for judging that the vehicle is in a preset working condition if the first air pressure is smaller than the second air pressure and the second air pressure is smaller than the third air pressure, and the gas in the crankcase is mixed with the air in the air filter through a pipeline.
Optionally, the preset crankcase ventilation system icing model is obtained through training of the following modules:
the system comprises a training data acquisition module, a control module and a control module, wherein the training data acquisition module is used for acquiring training data of a vehicle, the training data comprise second working condition data of the vehicle under a preset working condition and second vehicle running time corresponding to the second working condition data, the second working condition data comprise environment temperature, environment humidity, vehicle speed and crankcase ventilation quantity, and the preset working condition comprises that the environment temperature is in a preset temperature interval, the environment humidity is in a preset humidity interval and the vehicle speed is in a preset vehicle speed interval;
the training data processing module is used for acquiring actual icing data in the crankcase ventilation system corresponding to the second working condition data;
and the model training module is used for training a icing prediction model of the crankcase ventilation system according to the second working condition data and the corresponding actual icing data in the crankcase ventilation system.
Optionally, the prediction result execution module includes:
the first execution sub-module is used for outputting prompt information according to the prediction result;
and the second execution sub-module is used for executing the deicing function in the crankcase ventilation system according to the prediction result.
Optionally, the prediction result has a value for characterizing a degree of icing within the crankcase ventilation system, and the first execution submodule includes:
the first execution unit is used for outputting no prompt information if the icing degree value is smaller than a first icing threshold;
the second execution unit is used for reminding a user to adjust the running condition of the vehicle if the icing degree value is between the first icing threshold and the second icing threshold, wherein the first icing threshold is smaller than the second icing threshold;
and the third execution unit is used for reminding a user of paying attention to the parking information and executing the deicing function in the crankcase ventilation system of the vehicle if the icing degree value is larger than the second icing threshold value.
In another aspect, embodiments of the present invention also provide a vehicle including a processor, a memory, and a computer program stored on the memory and capable of running on the processor, which when executed by the processor, implements the steps of the method for predicting the icing level of a crankcase ventilation system of the vehicle.
In another aspect, embodiments of the present invention also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of a method of predicting the icing level of a crankcase ventilation system of a vehicle.
According to the embodiment of the invention, the first working condition data of the vehicle under the preset working condition is collected, the first vehicle running time corresponding to the first working condition data is determined, the first working condition data and the first vehicle running time are input into the preset icing prediction model of the crankcase ventilation system, and the obtained prediction result is used for representing the icing degree in the crankcase ventilation system. And the user knows the icing degree in the crankcase ventilation system according to the prediction result, so that corresponding treatment measures are taken to avoid the engine fault caused by serious icing in the crankcase ventilation system.
Drawings
FIG. 1 is a flow chart of steps of a method for predicting ice formation in a crankcase ventilation system of a vehicle according to an embodiment of the invention;
FIG. 2 is a schematic view of a portion of a crankcase ventilation system for a vehicle according to an embodiment of the invention;
fig. 3 is a block diagram of a device for predicting icing degree of a crankcase ventilation system of a vehicle according to an embodiment of the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to the appended drawings and appended detailed description. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
In cold areas in winter, such as northeast and northwest of China, the main reason for icing a vehicle crankcase ventilation system is that when a vehicle runs at a high speed under a low temperature and a high humidity environment for a long time and a large load, cold and hot air convection is generated between engine crankcase blowby gas (high-temperature and high-humidity gas) and fresh air at an air filter, so that the crankcase is sublimated and frozen, and the icing degree of the crankcase becomes serious along with the continuous time under the working condition, so that the crankcase and the engine are damaged. In the prior art, in order to avoid the blockage of the crankcase ventilation pipe caused by icing, some automobile manufacturers choose to add an electric heating device in the crankcase ventilation system, and the auxiliary heating of the electric heating device is utilized to effectively avoid the icing problem. However, the prior art lacks means for detecting or predicting the degree of ice formation in the crankcase.
Fig. 1 is a flowchart of steps of a method for predicting icing degree of a crankcase ventilation system of a vehicle according to an embodiment of the present invention, where the method includes:
step 101, when a vehicle is in a preset working condition, collecting first working condition data of the vehicle operation, and determining first vehicle operation time corresponding to the first working condition data, wherein the first working condition data comprises environment temperature, environment humidity, vehicle speed and crankcase ventilation;
fig. 2 is a schematic diagram of a part of a structure of a crankcase ventilation system of a vehicle provided in an embodiment of the present application, in which an air cleaner and a supercharger (not shown in the figure) are disposed on the vehicle, when an engine is running under a small load, crankcase gas enters an intake manifold through a part of a load oil-gas separation chamber, when the engine is running under a large load, the crankcase gas enters the intake manifold through a full load oil-gas separation chamber after being mixed with gas in the air cleaner, and icing condition in the air cleaner does not occur when the engine is running under the small load, so that the embodiment of the present invention considers that under the working condition of the large load, the supercharger starts to work, the supercharger is connected with the intake manifold, a great positive pressure is generated at the intake manifold, and the air leakage of the engine is relatively great during the large load running, and after the supercharger is started, a first air pressure P1 of the air cleaner, a second air pressure P2 of the crankcase of the vehicle, and a third air pressure P3 of the intake manifold are obtained, and at this time, the pressure distribution is: p3> P2> P1. The gas from the crankcase is directed to the rear end of the air cleaner via the oil and gas separation structure and the vent as shown by the arrows, and finally to the intake manifold.
Acquiring the speed of the vehicle before acquiring first working condition data of the vehicle operation, and starting the supercharger when the speed is greater than a preset speed; after the supercharger is started, acquiring first air pressure of an air filter, second air pressure of a crankcase of a vehicle and third air pressure of an air inlet manifold; if the first air pressure is smaller than the second air pressure and the second air pressure is smaller than the third air pressure, the air in the crankcase is mixed with the air in the air filter through the pipeline, and the vehicle is judged to be in a preset working condition. For example, when the vehicle is in a preset condition, the ambient temperature is typically below-20 degrees, the ambient humidity is typically 60% -80%, and the vehicle speed is typically greater than 100km/h.
102, inputting the first working condition data and the first vehicle running time into a preset crankcase ventilation system icing prediction model, and obtaining a prediction result according to the crankcase ventilation system icing prediction model, wherein the prediction result is used for representing the icing degree in the crankcase ventilation system;
the degree of icing within the crankcase ventilation system is related to ambient temperature, ambient humidity, vehicle speed, intake manifold pressure, crankcase pressure piston blow-by, vehicle run time, and the piping arrangement of the crankcase ventilation system. For the vehicle model using the same engine, the pipeline structure is the same, and is regarded as an unchanged factor, and the engine compartment thermal management and the crankcase pressure are not greatly changed. Thus, the first operating condition data collected includes ambient temperature, ambient humidity, vehicle speed, and crankcase blow-by.
After the first working condition data are collected, the first working condition data of the vehicle in the first vehicle running time are classified, a plurality of classes of target working condition data are obtained, and the vehicle speed is the same in the target working condition data of each class. For example, when the collected first working condition data is 20 minutes of the vehicle driving on the highway, the time interval is 15:16-15:36 pm, the ambient temperature is-30 degrees, the ambient humidity is 65%, the vehicle speed is 6 minutes at 105km/h, the vehicle speed is 2 minutes at 110km/h, the vehicle speed is 8 minutes at 112km/h, and the vehicle speed is 4 minutes at 115km/h, the first working condition data can be classified according to the vehicle speed to obtain four sets of target working condition data with the vehicle speeds of 105km/h, 110km/h, 112km/h and 115km/h respectively, and after the four sets of target working condition data are obtained, if the crankcase blow-by amount is different at the same vehicle speed, the four sets of target working condition data can be further classified according to the crankcase blow-by amount. When the first working condition data is classified, the first working condition data is further classified according to the ambient temperature and the ambient humidity, so that the corresponding relation between different working condition data and the icing degree in the crankcase ventilation system is conveniently established, and the prediction result is more accurate.
After target working condition data of a plurality of categories are obtained, the target working condition time corresponding to the target working condition data is counted. Inputting a plurality of target working condition data and a plurality of corresponding target working condition time into a preset icing prediction model of the crankcase ventilation system to obtain a plurality of target icing data which respectively correspond to the target working condition data, and carrying out accumulated summation on the plurality of target icing data to obtain integral icing data, wherein the integral icing data is a detection result. It should be noted that, the neural network model applied to data classification is a mature technology, and the icing prediction model of the crankcase ventilation system of the present application may be developed based on the neural network model applied to data classification, and the corresponding relations between the ambient temperature, the ambient humidity, the vehicle speed, the crankcase ventilation volume and the icing degree of the vehicle crankcase ventilation system are respectively established, so that the icing condition in the vehicle crankcase ventilation system can be predicted immediately after the first working condition data is obtained.
Exemplary, according to the collected first working condition data, after classifying the first working condition data, calculating a specific icing value I in unit time under a plurality of target working conditions and a corresponding vehicle running time t, and then carrying out accumulated summation:
overall icing degree = i1×t1+i2×t2+ … … +in×tn. After the data of the whole icing degree in the vehicle axle box ventilation system is obtained, the preset operation is executed according to the whole icing degree, so that the engine fault caused by excessive icing in the vehicle axle box ventilation system is prevented, and the use experience of a user is improved.
And 103, executing a preset operation according to the prediction result.
The step of executing the preset operation according to the prediction result comprises the following steps: and outputting prompt information according to the prediction result, and/or executing deicing function in the crankcase ventilation system according to the prediction result. The prompting information output according to the prediction result can be displayed in a text form or a picture form on a vehicle-mounted display, or the icing degree in the crankcase ventilation system can be prompted through voice, and when the total icing degree of the crankcase ventilation system of the vehicle reaches a preset threshold value, a driver is reminded, the vehicle speed is reduced, the running condition of the engine is adjusted, or a proper place is selected for stopping and resting.
According to the embodiment of the invention, the first working condition data of the vehicle under the preset working condition is collected, the first vehicle running time corresponding to the first working condition data is determined, the first working condition data and the first vehicle running time are input into the preset icing prediction model of the crankcase ventilation system, and the obtained prediction result is used for representing the icing degree in the crankcase ventilation system. And the user knows the icing degree in the crankcase ventilation system according to the prediction result, so that corresponding treatment measures are taken to avoid the engine fault caused by serious icing in the crankcase ventilation system.
In the embodiment of the invention, the process of training the icing model of the preset crankcase ventilation system comprises the following steps: acquiring training data of a vehicle, wherein the training data comprises second working condition data of the vehicle under a preset working condition and second vehicle running time corresponding to the second working condition data, the second working condition data comprises environment temperature, environment humidity, vehicle speed and crankcase blow-by amount, and the preset working condition comprises environment temperature in a preset temperature interval, environment humidity in a preset humidity interval and vehicle speed in a preset vehicle speed interval; and acquiring actual icing data in the crankcase ventilation system corresponding to the second working condition data, respectively establishing corresponding relations among the ambient temperature, the ambient humidity, the vehicle speed and the crankcase ventilation volume and the actual icing data in the crankcase ventilation system of the vehicle, and training an icing prediction model of the crankcase ventilation system according to the corresponding relations among the ambient temperature, the ambient humidity, the vehicle speed and the crankcase ventilation volume and the actual icing data in the crankcase ventilation system of the vehicle. The trained icing prediction model of the crankcase ventilation system can predict icing conditions in the crankcase ventilation system of the vehicle according to working condition data in the running process of the vehicle.
In an alternative embodiment, the icing degree value in the crankcase ventilation system represented by the prediction result has a first icing threshold and a second icing threshold, where the first icing threshold is smaller than the second icing threshold, and the first icing threshold may be 10% and the second icing threshold may be 20% as an example, and those skilled in the art may set the first icing threshold and the second icing threshold according to actual requirements. In the actual use process, if the icing degree value is smaller than the first icing threshold value, no prompt information is output; if the icing degree value is between the first icing threshold and the second icing threshold, reminding a user to adjust the running condition of the vehicle; and if the icing degree value is greater than the second icing threshold, reminding a user to pay attention to the parking message, and starting a deicing function in the crankcase ventilation system of the vehicle. By setting the threshold value of the icing degree in the crankcase ventilation system represented by the prediction result, a user can be effectively assisted to know the icing degree in the crankcase ventilation system, so that corresponding treatment measures are taken to avoid engine faults caused by serious icing in the crankcase ventilation system.
It should be noted that, for simplicity of description, the method embodiments are shown as a series of acts, but it should be understood by those skilled in the art that the embodiments are not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the embodiments. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred embodiments, and that the acts are not necessarily required by the embodiments of the invention.
In order to implement the method for predicting the icing degree of the crankcase ventilation system of the vehicle, fig. 3 is a schematic diagram of a device for predicting the icing degree of the crankcase ventilation system of the vehicle, which includes:
the data acquisition module 301 is configured to acquire first working condition data of a vehicle running when the vehicle is in a preset working condition, and determine a first vehicle running time corresponding to the first working condition data, where the first working condition data includes an ambient temperature, an ambient humidity, a vehicle speed and a crankcase ventilation;
the data processing module 302 is configured to input the first working condition data and the first vehicle running time into a preset icing prediction model of the crankcase ventilation system, and obtain a prediction result, where the prediction result is used to characterize the icing degree in the crankcase ventilation system; the method comprises the steps that a crankcase ventilation system icing prediction model is trained by adopting a neural network model, and the crankcase ventilation system icing prediction model is provided with a plurality of mapping relations between vehicle working condition data and the icing degree of the crankcase ventilation system of the vehicle;
the prediction result execution module 303 is configured to execute a preset operation according to the prediction result.
In an alternative embodiment, the data processing module 302 may include:
the working condition data classification sub-module is used for classifying first working condition data of the vehicle in the first vehicle running time to obtain target working condition data of a plurality of categories, and the vehicle speed and the crankcase gas channeling are the same in the target working condition data of each category;
the working condition operation time statistics sub-module is used for counting target working condition time corresponding to the target working condition data;
the working condition data processing sub-module is used for inputting a plurality of target working condition data and a plurality of corresponding target working condition time into a preset icing prediction model of the crankcase ventilation system, and obtaining a prediction result.
In an alternative embodiment, the operating condition data processing sub-module may include:
the target icing data acquisition unit is used for inputting a plurality of target working condition data and a plurality of corresponding target working condition time into a preset crankcase ventilation system icing prediction model to obtain a plurality of target icing data corresponding to the target working condition data respectively;
the whole icing data acquisition unit is used for carrying out accumulated summation on a plurality of target icing data to obtain whole icing data;
and the prediction result confirming unit is used for confirming that the whole icing data is the detection result.
In an alternative embodiment, the vehicle is provided with an air filter and a supercharger, and the device may further comprise, before collecting the first operating condition data of the vehicle operation:
the vehicle speed acquisition module is used for acquiring the vehicle speed of the vehicle;
the supercharger control module is used for starting the supercharger when the vehicle speed is greater than a preset vehicle speed;
the air pressure acquisition module is used for acquiring the first air pressure of the air filter, the second air pressure of the crankcase of the vehicle and the third air pressure of the air inlet manifold after the supercharger is started;
and the vehicle operation condition judging module is used for judging that the vehicle is in a preset working condition if the first air pressure is smaller than the second air pressure and the second air pressure is smaller than the third air pressure, and the gas in the crankcase is mixed with the air in the air filter through a pipeline.
In an alternative embodiment, the preset crankcase ventilation icing model is trained by the following modules:
the system comprises a training data acquisition module, a control module and a control module, wherein the training data acquisition module is used for acquiring training data of a vehicle, the training data comprise second working condition data of the vehicle under a preset working condition and second vehicle running time corresponding to the second working condition data, the second working condition data comprise environment temperature, environment humidity, vehicle speed and crankcase ventilation quantity, and the preset working condition comprises that the environment temperature is in a preset temperature interval, the environment humidity is in a preset humidity interval and the vehicle speed is in a preset vehicle speed interval;
the training data processing module is used for acquiring actual icing data in the crankcase ventilation system corresponding to the second working condition data;
and the model training module is used for training a icing prediction model of the crankcase ventilation system according to the second working condition data and the corresponding actual icing data in the crankcase ventilation system.
In an alternative embodiment, the prediction result execution module 303 may include:
the first execution sub-module is used for outputting prompt information according to the prediction result;
and the second execution sub-module is used for executing the deicing function in the crankcase ventilation system according to the prediction result.
In an alternative embodiment, the prediction result has a value for characterizing a degree of icing within the crankcase ventilation system, the first execution submodule comprising:
the first execution unit is used for outputting no prompt information if the icing degree value is smaller than a first icing threshold;
the second execution unit is used for reminding a user to adjust the running condition of the vehicle if the icing degree value is between the first icing threshold and the second icing threshold, wherein the first icing threshold is smaller than the second icing threshold;
and the third execution unit is used for reminding a user of paying attention to the parking information and executing the deicing function in the crankcase ventilation system of the vehicle if the icing degree value is larger than the second icing threshold value.
According to the embodiment of the invention, the first working condition data of the vehicle under the preset working condition is collected, the first vehicle running time corresponding to the first working condition data is determined, the first working condition data and the first vehicle running time are input into the preset icing prediction model of the crankcase ventilation system, the obtained prediction result is used for representing the icing degree in the crankcase ventilation system, and a user knows the icing degree in the crankcase ventilation system according to the prediction result, so that corresponding treatment measures are taken, and engine faults caused by serious icing in the crankcase ventilation system are avoided.
In another aspect, embodiments of the present invention also provide a vehicle including a processor, a memory, and a computer program stored on the memory and capable of running on the processor, which when executed by the processor, implements the steps of the method for predicting the icing level of a crankcase ventilation system of the vehicle.
In another aspect, embodiments of the present invention also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of a method of predicting the icing level of a crankcase ventilation system of a vehicle.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described by differences from other embodiments, and identical and similar parts between the embodiments are all enough to be referred to each other.
It will be apparent to those skilled in the art that embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the invention may take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
Embodiments of the present invention are described with reference to flowchart illustrations and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing terminal device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing terminal device, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiment and all such alterations and modifications as fall within the scope of the embodiments of the invention.
Finally, it is further noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or terminal. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or terminal device comprising the element.
The above description of the method for predicting the icing degree of the crankcase ventilation system of the vehicle and the device for predicting the icing degree of the crankcase ventilation system of the vehicle provided by the invention applies specific examples to illustrate the principles and the implementation of the invention, and the above examples are only used for helping to understand the method and the core idea of the invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.
Claims (10)
1. A method for predicting the icing level of a crankcase ventilation system of a vehicle, comprising:
when a vehicle is in a preset working condition, first working condition data of the vehicle operation are collected, and first vehicle operation time corresponding to the first working condition data is determined, wherein the first working condition data comprise ambient temperature, ambient humidity, vehicle speed and crankcase ventilation;
inputting the first working condition data and the first vehicle running time into a preset crankcase ventilation system icing prediction model, and obtaining a prediction result according to the crankcase ventilation system icing prediction model, wherein the prediction result is used for representing the icing degree in the crankcase ventilation system; the method comprises the steps that a crankcase ventilation system icing prediction model is trained by adopting a neural network model, and the crankcase ventilation system icing prediction model is provided with a plurality of mapping relations between vehicle working condition data and the icing degree of a crankcase ventilation system of a vehicle;
and executing preset operation according to the prediction result.
2. The method of claim 1, wherein the inputting the first operating condition data and the first vehicle operating time into a predetermined crankcase ventilation system icing prediction model and deriving a prediction result based on the crankcase ventilation system icing prediction model comprises:
classifying the first working condition data of the vehicle in the first vehicle running time to obtain target working condition data of a plurality of categories, wherein the vehicle speed and the crankcase gas channeling are the same in the target working condition data of each category;
counting target working condition time corresponding to the target working condition data;
and inputting the target working condition data and the corresponding target working condition time into a preset icing prediction model of the crankcase ventilation system, and obtaining a prediction result.
3. The method according to claim 2, wherein the inputting the plurality of target operating condition data and the corresponding plurality of target operating conditions into the preset crankcase ventilation system icing prediction model, and obtaining the prediction result, includes:
inputting a plurality of target working condition data and a plurality of corresponding target working condition times into a preset crankcase ventilation system icing prediction model to obtain a plurality of target icing data corresponding to the target working condition data respectively;
accumulating and summing a plurality of target icing data to obtain integral icing data;
and determining the whole icing data as the prediction result.
4. The method of claim 1, wherein the vehicle is provided with an air cleaner and a supercharger, and wherein prior to collecting the first operating condition data for vehicle operation, the method further comprises:
acquiring the speed of a vehicle;
when the vehicle speed is greater than a preset vehicle speed, starting the supercharger;
after the supercharger is started, acquiring first air pressure of the air filter, second air pressure of a crankcase of a vehicle and third air pressure of an intake manifold;
and if the first air pressure is smaller than the second air pressure and the second air pressure is smaller than the third air pressure, the air in the crankcase is mixed with the air in the air filter through the pipeline, and the vehicle is judged to be in a preset working condition.
5. The method of claim 1, wherein training the pre-set crankcase ventilation system icing model comprises:
acquiring training data of a vehicle, wherein the training data comprises second working condition data of the vehicle under a preset working condition and second vehicle running time corresponding to the second working condition data, the second working condition data comprises environment temperature, environment humidity, vehicle speed and crankcase blow-by amount, and the preset working condition comprises environment temperature in a preset temperature interval, environment humidity in a preset humidity interval and vehicle speed in a preset vehicle speed interval;
acquiring actual icing data in a crankcase ventilation system corresponding to the second working condition data;
and training a crankcase ventilation system icing prediction model according to the second working condition data and the actual icing data in the corresponding crankcase ventilation system.
6. The method of claim 1, wherein the performing a preset operation according to the prediction result comprises:
outputting prompt information according to the prediction result;
and/or performing a de-icing function within the crankcase ventilation system based on the prediction.
7. The method of claim 6, wherein the prediction result has a icing level value for characterizing the crankcase ventilation system, and wherein outputting a hint based on the prediction result comprises:
if the icing degree value is smaller than the first icing threshold, not outputting prompt information;
reminding a user to adjust the running condition of the vehicle if the icing degree value is between the first icing threshold and the second icing threshold, wherein the first icing threshold is smaller than the second icing threshold;
and if the icing degree value is larger than the second icing threshold, reminding a user to pay attention to the parking information, and executing the deicing function in the crankcase ventilation system of the vehicle.
8. A vehicle crankcase ventilation system icing level prediction apparatus, comprising:
the data acquisition module is used for acquiring first working condition data of vehicle operation when the vehicle is in a preset working condition, and determining first vehicle operation time corresponding to the first working condition data, wherein the first working condition data comprises ambient temperature, ambient humidity, vehicle speed and crankcase blow-by;
the data processing module is used for inputting the first working condition data and the first vehicle running time into a preset crankcase ventilation system icing prediction model, obtaining a prediction result according to the crankcase ventilation system icing prediction model, and the prediction result is used for representing the icing degree in the crankcase ventilation system; the method comprises the steps that a crankcase ventilation system icing prediction model is trained by adopting a neural network model, and the crankcase ventilation system icing prediction model is provided with a plurality of mapping relations between vehicle working condition data and the icing degree of a crankcase ventilation system of a vehicle;
and the prediction result execution module is used for executing preset operation according to the prediction result.
9. A vehicle, characterized by comprising: a processor, a memory and a computer program stored on the memory and capable of running on the processor, which when executed by the processor performs the steps of the method according to any of claims 1-7.
10. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the method according to any of claims 1-7.
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| CN202210917668.7A CN117552854A (en) | 2022-08-01 | 2022-08-01 | Method and device for predicting icing degree of crankcase ventilation system of vehicle |
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| CN202210917668.7A CN117552854A (en) | 2022-08-01 | 2022-08-01 | Method and device for predicting icing degree of crankcase ventilation system of vehicle |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116085127A (en) * | 2023-02-20 | 2023-05-09 | 重庆长安汽车股份有限公司 | Anti-icing control method, device and storage medium for crankcase ventilation system |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116085127A (en) * | 2023-02-20 | 2023-05-09 | 重庆长安汽车股份有限公司 | Anti-icing control method, device and storage medium for crankcase ventilation system |
| CN116085127B (en) * | 2023-02-20 | 2025-01-28 | 重庆长安汽车股份有限公司 | A crankcase ventilation system anti-icing control method, device and storage medium |
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