CN110607970A - Control method for intelligent opening and closing of automobile main driving window - Google Patents

Control method for intelligent opening and closing of automobile main driving window Download PDF

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Publication number
CN110607970A
CN110607970A CN201910893147.0A CN201910893147A CN110607970A CN 110607970 A CN110607970 A CN 110607970A CN 201910893147 A CN201910893147 A CN 201910893147A CN 110607970 A CN110607970 A CN 110607970A
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CN
China
Prior art keywords
window
opening
closing
jumping
closing degree
Prior art date
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Pending
Application number
CN201910893147.0A
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Chinese (zh)
Inventor
唐竞
林长波
秦炎炎
蔡其瑾
吴斌
秦刚
刘冰莹
欧增开
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Dongfeng Liuzhou Motor Co Ltd
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Dongfeng Liuzhou Motor Co Ltd
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Publication date
Application filed by Dongfeng Liuzhou Motor Co Ltd filed Critical Dongfeng Liuzhou Motor Co Ltd
Priority to CN201910893147.0A priority Critical patent/CN110607970A/en
Publication of CN110607970A publication Critical patent/CN110607970A/en
Pending legal-status Critical Current

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Classifications

    • E—FIXED CONSTRUCTIONS
    • E05—LOCKS; KEYS; WINDOW OR DOOR FITTINGS; SAFES
    • E05F—DEVICES FOR MOVING WINGS INTO OPEN OR CLOSED POSITION; CHECKS FOR WINGS; WING FITTINGS NOT OTHERWISE PROVIDED FOR, CONCERNED WITH THE FUNCTIONING OF THE WING
    • E05F15/00—Power-operated mechanisms for wings
    • E05F15/60—Power-operated mechanisms for wings using electrical actuators
    • E05F15/603—Power-operated mechanisms for wings using electrical actuators using rotary electromotors
    • E05F15/665—Power-operated mechanisms for wings using electrical actuators using rotary electromotors for vertically-sliding wings
    • E05F15/689—Power-operated mechanisms for wings using electrical actuators using rotary electromotors for vertically-sliding wings specially adapted for vehicle windows
    • E05F15/695—Control circuits therefor
    • E—FIXED CONSTRUCTIONS
    • E05—LOCKS; KEYS; WINDOW OR DOOR FITTINGS; SAFES
    • E05F—DEVICES FOR MOVING WINGS INTO OPEN OR CLOSED POSITION; CHECKS FOR WINGS; WING FITTINGS NOT OTHERWISE PROVIDED FOR, CONCERNED WITH THE FUNCTIONING OF THE WING
    • E05F15/00—Power-operated mechanisms for wings
    • E05F15/70—Power-operated mechanisms for wings with automatic actuation
    • E—FIXED CONSTRUCTIONS
    • E05—LOCKS; KEYS; WINDOW OR DOOR FITTINGS; SAFES
    • E05F—DEVICES FOR MOVING WINGS INTO OPEN OR CLOSED POSITION; CHECKS FOR WINGS; WING FITTINGS NOT OTHERWISE PROVIDED FOR, CONCERNED WITH THE FUNCTIONING OF THE WING
    • E05F15/00—Power-operated mechanisms for wings
    • E05F15/70—Power-operated mechanisms for wings with automatic actuation
    • E05F15/71—Power-operated mechanisms for wings with automatic actuation responsive to temperature changes, rain, wind or noise
    • E—FIXED CONSTRUCTIONS
    • E05—LOCKS; KEYS; WINDOW OR DOOR FITTINGS; SAFES
    • E05Y—INDEXING SCHEME RELATING TO HINGES OR OTHER SUSPENSION DEVICES FOR DOORS, WINDOWS OR WINGS AND DEVICES FOR MOVING WINGS INTO OPEN OR CLOSED POSITION, CHECKS FOR WINGS AND WING FITTINGS NOT OTHERWISE PROVIDED FOR, CONCERNED WITH THE FUNCTIONING OF THE WING
    • E05Y2900/00—Application of doors, windows, wings or fittings thereof
    • E05Y2900/50—Application of doors, windows, wings or fittings thereof for vehicles
    • E05Y2900/53—Application of doors, windows, wings or fittings thereof for vehicles characterised by the type of wing
    • E05Y2900/55—Windows

Landscapes

  • Power-Operated Mechanisms For Wings (AREA)

Abstract

The invention discloses a method for controlling intelligent opening and closing of a main driving window of an automobile. When the arrays in the data set reach 100, 90 of the arrays are randomly selected as training sets to serve as training sets of the back propagation neural network, the remaining 10 arrays serve as prediction sets, functions tan sig (x) =2/(1+ exp (-2 × n)) -1 are selected as transfer functions between an input layer and a hidden layer of the back propagation neural system, purelin (x) = x functions are selected as output layer functions, and the number of nodes of the hidden layer is 7; and taking the converged environment and the corresponding model of the opening and closing degree of the main driving window after training as a new prediction model. The invention can solve the problem that the prior art can not change the own switching strategy in a self-adaptive manner. The problem of potential safety hazard exists in personnel's personal safety in the car because driver's attention is not concentrated because of the relapse switching door window.

Description

Control method for intelligent opening and closing of automobile main driving window
Technical Field
The invention relates to the technical field of automobile manufacturing, in particular to a control method for intelligent opening and closing of an automobile main driving window.
Background
With the higher consumption level of consumers, the number of automobiles owned by a family is more and more, and meanwhile, the requirements of the consumers on the comfort and the intellectualization of the automobiles are also higher and more. The driver is at the in-process of traveling, thereby improves car internal environment and driving experience through switching car owner driving door window usually, for having guaranteed the good driving environment of driver and driving experience, the driver can switch owner driving door window usually, but present car door window still has the not high problem of intelligent degree, and the opening and closing degree of driver's disposable adjustment door window often can make the driver be in the most comfortable driving environment through the opening and closing degree of adjustment owner driving door window many times. There are some window opening and closing systems with low intelligence, that is, under the severe environment, the window is automatically closed, but under the mild environment, the driver still needs to manually adjust the opening and closing degree of the main driving window, and at the same time, these systems cannot adaptively change the own opening and closing strategy. Repeated opening and closing of the vehicle window causes the inattention of a driver, and the personal safety of people in the vehicle is caused to have potential safety hazards.
Disclosure of Invention
The invention aims to provide a control method for intelligent opening and closing of a main driving window of an automobile, which can solve the problem that the prior art can not change the opening and closing strategy of the automobile in a self-adaptive manner. The problem of potential safety hazard exists in personnel's personal safety in the car because driver's attention is not concentrated because of the relapse switching door window.
In order to solve the problems, the invention adopts the technical scheme that: the control method for the intelligent opening and closing of the main driving car window of the automobile is realized by adopting a control system for the intelligent opening and closing of the driving car window of the automobile, and the control system comprises a car window controller, wherein the car window controller receives detection environment information of a temperature sensor, an air quality sensor, a sound sensor and a light intensity sensor and controls the opening and closing degree of the car window according to the environment information; the control method comprises the following steps:
(1) the driver turns on an ignition switch;
(2) starting the intelligent opening and closing system of the main driving window of the automobile;
(3) the vehicle window controller waits for a manual operation signal, and each sensor acquires the information of the internal environment and the external environment of the vehicle;
(4) the vehicle window controller receives and stores the signal of the sensor, namely the vehicle internal and external environment information;
(5) comparing the information of the inside and outside environment of the vehicle with a model embedded in the vehicle window controller and outputting the opening and closing degree of the vehicle window;
(6) detecting whether the vehicle window is in a closed state, and jumping to the step (8) if not;
(7) closing the skylight, detecting a manual control signal of the vehicle window, jumping to the step (7-a) if the manual control signal exists, and jumping to the step (7-b) if the manual control signal does not exist;
(7-a) manually controlling the opening and closing degree of a main driving window, storing the final opening and closing degree and the environmental information into a ROM of the window controller for data collection, judging whether effective data in the data collection reach 100 groups or not, and jumping to a step 12 if the effective data in the data collection reach 100 groups;
(7-b) the window controller directly controls the opening and closing degree of the main driving window, and then the step (3) is skipped;
(8) if the skylight is not closed, namely the opening and closing degree is not 0, calculating the difference B between the current opening and closing degree and the opening and closing degree output by the model;
(9) comparing the difference B with a preset opening and closing degree difference A, jumping to the step (10) if A is less than B, and jumping to the step (11) if A is greater than B;
(10) detecting whether a manual control signal exists in the vehicle window, jumping to the step (10-a) if the manual control signal exists, and jumping to the step (10-b) if the manual control signal does not exist;
(10-a), manually controlling the opening and closing degree of the main driving window, storing the final opening and closing degree and the data of the environmental information into a ROM of the window controller for concentration, judging whether the effective data of the data set reaches 100 groups, and jumping to the step (12) if the effective data of the data set reaches 100 groups;
(10-b), the window controller directly controls the opening and closing degree of the main driving window, and then jumping to the step (3);
(11) detecting a manual control signal of the vehicle window, jumping to the step (11-a) if the manual control signal exists, and jumping to the step (11-b) if the manual control signal does not exist;
(11-a) manually controlling the opening and closing degree of the main driving window, and storing the final opening and closing degree and the data of the environment information into a ROM of the window controller for concentration; judging whether the array effective data reach 100 groups, and jumping to the step (12) if the array effective data reach 100 groups;
(11-b) maintaining a current window opening and closing degree, preventing a window motor from continuously moving, thereby reducing the window motor life;
(12) when the number of the arrays in the data set reaches 100, randomly selecting 90 of the arrays as a training set of a back propagation neural network, selecting 10 of the rest arrays as a prediction set, selecting a tansig (x) =2/(1+ exp (-2 x n)) -1 function as a transfer function between an input layer and a hidden layer of the back propagation neural system, selecting a purelin (x) = x function as an output layer function, and setting the number of nodes of the hidden layer to be 7; and (5) taking the converged environment and the corresponding model of the opening and closing degree of the main driving window after training as a new prediction model in the step 5.
In the above technical solution, a more specific solution may also be: the temperature sensor comprises an inside temperature sensor and an outside temperature sensor.
Further: the air quality sensor comprises an air quality sensor inside the vehicle and an air quality sensor outside the vehicle.
Further: the sound sensor is a sound sensor outside the vehicle.
Due to the adoption of the technical scheme, compared with the prior art, the invention has the beneficial effects that: according to the invention, the back propagation neural network is established in the vehicle window controller, the corresponding models of the environment and the opening and closing degree of the vehicle window are established in the back propagation neural network, and the prediction model is embedded in the vehicle window controller. The environmental information collected by the sensor is used as an input layer of the back propagation neural network, the output layer is the opening and closing degree of the main driving window, so that the knowing and the enabling of the opening and closing control of the main driving window are improved, the attention of a driver can be focused on safely driving the vehicle, and the potential safety hazard caused by repeated opening and closing of the window of the driver is avoided.
Drawings
FIG. 1 is a block diagram of the structure of the present invention.
Fig. 2 is a diagram of a back propagation neural network model architecture of the present invention.
Detailed Description
The invention is described in more detail below with reference to the following figures and examples:
the method for controlling the intelligent opening and closing of the main driving window of the automobile shown in fig. 1 and 2 is implemented by using a control system for the intelligent opening and closing of the driving window of the automobile, wherein the control system comprises a window controller 6, and the window controller receives the detection environment information of a temperature sensor, an air quality sensor, a sound sensor and a light intensity sensor 5 and controls the opening and closing degree of the window according to the environment information; the control method comprises the following steps:
(1) the driver turns on an ignition switch;
(2) starting the intelligent opening and closing system of the main driving window of the automobile;
(3) the vehicle window controller 6 waits for a manual operation signal, and each sensor acquires the information of the internal environment and the external environment of the vehicle;
(4) the vehicle window controller 6 receives and stores the manual operation signal and the vehicle interior and exterior environment information acquired by the sensor;
(5) comparing the information of the inside and outside environment of the vehicle with a model embedded in the vehicle window controller 6 and outputting the opening and closing degree of the vehicle window;
(6) detecting whether the vehicle window is in a closed state, and jumping to the step (8) if not;
(7) closing the skylight, detecting a manual control signal of the vehicle window, jumping to the step (7-a) if the manual control signal exists, and jumping to the step (7-b) if the manual control signal does not exist;
(7-a) manually controlling the opening and closing degree of the main driving window, storing the final opening and closing degree and the environmental information into a ROM of the window controller 6 for data collection, judging whether effective data in the data collection reach 100 groups or not, and jumping to a step 12 if the effective data in the data collection reach 100 groups;
(7-b), directly controlling the opening and closing degree of the main driving window by the window controller 6, and jumping to the step (3);
(8) if the skylight is not closed, namely the opening degree is not 0, calculating the difference B between the current opening degree and the opening degree output by the model;
(9) comparing the difference B with a preset opening and closing degree difference A, jumping to the step (10) if A is less than B, and jumping to the step (11) if A is greater than B;
(10) detecting whether the vehicle window has a manual control signal, if so, jumping to the step (10-a), and if not, jumping to the step (10-b);
(10-a) manually controlling the opening and closing degree of the main driving window, storing the final opening and closing degree and the data of the environmental information into a ROM of a window controller 6 for concentration, judging whether the effective data of the data set reaches 100 groups, and jumping to the step (12) if the effective data of the data set reaches 100 groups;
(10-b), directly controlling the opening and closing degree of the main driving window by the window controller 6, and jumping to the step (3);
(11) detecting a manual control signal of the vehicle window, jumping to the step (11-a) if the manual control signal exists, and jumping to the step (11-b) if the manual control signal does not exist;
(11-a) manually controlling the opening and closing degree of the main driving window, and storing the final opening and closing degree and the data of the environmental information into a ROM of the window controller 6 for concentration; judging whether the array effective data reach 100 groups, and jumping to the step (12) if the array effective data reach 100 groups;
(11-b) maintaining the current window opening and closing degree, and preventing the window motor 7 from continuously moving, thereby reducing the service life of the window motor 7;
(12) and when the array in the data set reaches 100 groups, randomly selecting 90 groups as a training set of a back propagation neural network, using the remaining 10 groups as a prediction set, establishing a corresponding model of the environment and the opening and closing degree of the window in the back propagation neural network, and embedding the prediction model into a window controller. The method comprises the steps that environmental information collected by a sensor is used as an input layer of a back propagation neural network, an output layer is the opening and closing degree of a main driving window, a tan sig (x) =2/(1+ exp (-2 x n)) -1 function is selected as a transfer function between the input layer and a hidden layer of the back propagation neural system, a purelin (x) = x function is selected as an output layer function, and the number of nodes of the hidden layer is 7; the corresponding model of the convergence environment and the opening and closing degree of the main driving window after training is used as a new prediction model in step 5, as shown in fig. 2, the number of nodes of the input layer in fig. 2 is 6, the number of nodes of the hidden layer is 7, the number of nodes of the output layer is 1, bn in fig. 2 is the threshold value of the nth node of the hidden layer, WmnIs the weight from the m-th node of the input layer to the n-th node of the hidden layer, b0Threshold value of output layer node, WnjIs the weight from the nth node of the hidden layer to the jth node of the output layer, and Y is the output value.
In the present embodiment, the temperature sensors include an in-vehicle temperature sensor 1 and an out-vehicle temperature sensor 2; the air quality sensor comprises an air quality sensor 3 inside the vehicle and an air quality sensor 4 outside the vehicle; the sound sensor is a vehicle exterior sound sensor 8.
The invention provides a control method for intelligently changing the opening and closing degree of a vehicle window according to the environment aiming at changing the opening and closing degree of the vehicle window by manually and repeatedly opening and closing the vehicle window by a driver, so that the environment in a vehicle is automatically improved, and potential safety hazards are avoided. According to the method, the back propagation neural network in machine learning is selected to establish the model, the environment based on the back propagation neural network and the corresponding model of the opening and closing of the vehicle window are established, the driver can learn that the opening and closing degree of the vehicle window is different and the model is updated most comfortably under different environments, and the system intelligence degree is high. Under the condition that the driver changes, the method can automatically learn the preference habit of the driver on the environment and the opening and closing degree, automatically improve the model corresponding to the environment and the opening and closing degree of the main driving window, and has high system intelligence degree.

Claims (4)

1. The utility model provides a control method of car owner's driving door window intelligence switching which characterized in that: the intelligent opening and closing control system for the driving of the automobile window is adopted for realizing, and comprises a window controller, wherein the window controller receives detection environment information of a temperature sensor, an air quality sensor, a sound sensor and a light intensity sensor and controls the opening and closing degree of the window according to the environment information; the control method comprises the following steps:
(1) the driver turns on an ignition switch;
(2) starting the intelligent opening and closing system of the main driving window of the automobile;
(3) the vehicle window controller waits for a manual operation signal, and each sensor acquires the information of the internal environment and the external environment of the vehicle;
(4) the vehicle window controller receives and stores the signal of the sensor, namely the vehicle internal and external environment information;
(5) comparing the information of the inside and outside environment of the vehicle with a model embedded in the vehicle window controller and outputting the opening and closing degree of the vehicle window;
(6) detecting whether the vehicle window is in a closed state, and jumping to the step (8) if not;
(7) closing the skylight, detecting a manual control signal of the vehicle window, jumping to the step (7-a) if the manual control signal exists, and jumping to the step (7-b) if the manual control signal does not exist;
(7-a) manually controlling the opening and closing degree of a main driving window, storing the final opening and closing degree and the environmental information into a ROM of the window controller for data collection, judging whether effective data in the data collection reach 100 groups or not, and jumping to a step 12 if the effective data in the data collection reach 100 groups;
(7-b) the window controller directly controls the opening and closing degree of the main driving window, and then the step (3) is skipped;
(8) if the skylight is not closed, namely the opening and closing degree is not 0, calculating the difference B between the current opening and closing degree and the opening and closing degree output by the model;
(9) comparing the difference B with a preset opening and closing degree difference A, jumping to the step (10) if A is less than B, and jumping to the step (11) if A is greater than B;
(10) detecting whether a manual control signal exists in the vehicle window, jumping to the step (10-a) if the manual control signal exists, and jumping to the step (10-b) if the manual control signal does not exist;
(10-a), manually controlling the opening and closing degree of the main driving window, storing the final opening and closing degree and the data of the environmental information into a ROM of the window controller for concentration, judging whether the effective data of the data set reaches 100 groups, and jumping to the step (12) if the effective data of the data set reaches 100 groups;
(10-b), the window controller directly controls the opening and closing degree of the main driving window, and then jumping to the step (3);
(11) detecting a manual control signal of the vehicle window, jumping to the step (11-a) if the manual control signal exists, and jumping to the step (11-b) if the manual control signal does not exist;
(11-a) manually controlling the opening and closing degree of the main driving window, and storing the final opening and closing degree and the data of the environment information into a ROM of the window controller for concentration; judging whether the array effective data reach 100 groups, and jumping to the step (12) if the array effective data reach 100 groups;
(11-b) maintaining a current window opening and closing degree, preventing a window motor from continuously moving, thereby reducing the window motor life;
(12) when the number of the arrays in the data set reaches 100, randomly selecting 90 of the arrays as a training set of a back propagation neural network, selecting 10 of the rest arrays as a prediction set, selecting a tansig (x) =2/(1+ exp (-2 x n)) -1 function as a transfer function between an input layer and a hidden layer of the back propagation neural system, selecting a purelin (x) = x function as an output layer function, and setting the number of nodes of the hidden layer to be 7; and (5) taking the converged environment and the corresponding model of the opening and closing degree of the main driving window after training as a new prediction model in the step 5.
2. The method for controlling intelligent opening and closing of the automobile main driving window according to claim 1, characterized by comprising the following steps of: the temperature sensor comprises an inside temperature sensor and an outside temperature sensor.
3. The method for controlling intelligent opening and closing of the automobile main driving window according to claim 1 or 2, characterized in that: the air quality sensor comprises an air quality sensor inside the vehicle and an air quality sensor outside the vehicle.
4. The method for controlling intelligent opening and closing of the automobile main driving window according to claim 1 or 2, characterized in that: the sound sensor is a sound sensor outside the vehicle.
CN201910893147.0A 2019-09-20 2019-09-20 Control method for intelligent opening and closing of automobile main driving window Pending CN110607970A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11794676B1 (en) 2022-12-14 2023-10-24 Mercedes-Benz Group AG Computing systems and methods for generating user-specific automated vehicle actions using artificial intelligence

Citations (5)

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Publication number Priority date Publication date Assignee Title
KR20000055779A (en) * 1999-02-10 2000-09-15 정몽규 Window open/close system of vehicles
CN105625859A (en) * 2014-10-31 2016-06-01 大陆汽车电子(长春)有限公司 Self-adaptive car window position adjusting method and car window controller
CN106114133A (en) * 2016-07-13 2016-11-16 乐视控股（北京）有限公司 A kind of control method for vehicle and device
CN106223771A (en) * 2016-08-26 2016-12-14 宁波博报门窗有限公司 A kind of smart window and control method thereof
CN107220613A (en) * 2017-05-24 2017-09-29 郑勇 Multifunctional control method based on image procossing

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20000055779A (en) * 1999-02-10 2000-09-15 정몽규 Window open/close system of vehicles
CN105625859A (en) * 2014-10-31 2016-06-01 大陆汽车电子(长春)有限公司 Self-adaptive car window position adjusting method and car window controller
CN106114133A (en) * 2016-07-13 2016-11-16 乐视控股（北京）有限公司 A kind of control method for vehicle and device
CN106223771A (en) * 2016-08-26 2016-12-14 宁波博报门窗有限公司 A kind of smart window and control method thereof
CN107220613A (en) * 2017-05-24 2017-09-29 郑勇 Multifunctional control method based on image procossing

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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Application publication date: 20191224