CN106980313B - A car driving style optimization system and optimization method - Google Patents

Abstract

The application discloses an automobile driving mode optimizing system and an optimizing method. The system comprises a singlechip, an automobile OBD data reading module, a GPS satellite positioning module, a GPRS wireless transmission module, a Bluetooth module, an automobile driving habit optimization module, a GPRS wireless receiver, an antenna, a Bluetooth receiver, a display screen, a loudspeaker, a cloud server, a cloud database and a mobile phone terminal. The system can optimize the driving habit of a driver, provides an effective solution to the bad driving habit, feeds back and records instant data in a cloud database, analyzes and predicts various faults of different vehicles caused by the bad driving habit through big data, influences of the driving habits of different crowds on the automobile fault rate, and provides a solution to the faults.

Description

A car driving style optimization system and optimization method

Technical field

The invention relates to the field of automobiles, and specifically relates to an automobile driving mode optimization system and an optimization method.

Background technique

With the rapid development of China's economy, the number of automobiles in our country is increasing year by year. At the same time, the pressure caused by automobile fuel consumption and exhaust emissions is also increasing. Energy conservation and emission reduction have attracted more and more attention. The driver is the main body of car control, and the driver's driving behavior and driving habits have a great impact on the car's fuel consumption. Moreover, with the development of science and technology, vehicle-mounted fault diagnosis systems have emerged, gradually replacing traditional fault diagnosis equipment and enabling remote detection of vehicle faults. Combined with big data, more advanced technology can be used to analyze and optimize the fuel consumption problems caused by driving habits and other behaviors to achieve the purpose of reducing car maintenance costs and reducing environmental pressure.

Application number 201620936849.4 discloses a car status prediction system based on the Internet of Things. The system can monitor the electronic and mechanical faults of the car. It can also classify the monitoring data and save it through network processing. It can draw the usage curve of each component of the tested car, collect car data, and compare it with the usage curve of each component of the brand model under big data. , it can predict the use status and service life of various car parts under various working conditions, remind users in advance to repair the car, replace relevant accessories, take precautions in advance, and improve driving safety. However, this literature starts from car faults and does not propose an optimization method for driver habits.

Contents of the invention

In view of the shortcomings of the existing technology, the technical problem to be solved by the present invention is to provide a vehicle driving mode optimization system and optimization method. This method generates driving habit optimization reports for different cars and different drivers through the analysis and sorting of the optimization system, reducing failure rates, reducing fuel consumption, and reducing car maintenance costs.

The technical solution of the present invention to solve the technical problems of the system is to provide a car driving mode optimization system, which is characterized in that the system includes a single-chip microcomputer, a car OBD data reading module, a GPS satellite positioning module, a GPRS wireless transmission module, and a Bluetooth module. Car driving habit optimization module, GPRS wireless receiver, antenna, Bluetooth receiver, display screen, speaker, cloud server, cloud database and mobile phone terminal;

The single-chip microcomputer is respectively connected with the car OBD data reading module, GPS satellite positioning module, GPRS wireless transmission module, Bluetooth module and car driving habit optimization module; the car OBD data reading module is connected with the car OBD; the GPS satellite positioning The module is connected to the antenna and receives satellite signals through the antenna; the GPRS wireless transmission module is connected to the GPRS wireless receiver; the Bluetooth module is connected to the mobile phone terminal through the Bluetooth receiver; the cloud server is connected to the GPRS wireless receiver and the cloud database respectively. Connection; the car driving habit optimization module is connected to the display screen and the speaker respectively.

The technical solution of the present invention to solve the technical problems of the method is to provide a method for optimizing the driving style of a car, which is characterized by including the following steps:

(1) The microcontroller controls the car's OBD data reading module and extracts the parameter information during car operation through the car's CAN bus protocol;

(2) Transmit parameter information to the cloud server through the GPRS wireless transmission module and GPRS wireless receiver and store it in the cloud database;

(3) In the cloud database, the car model and parameter information transmitted by the GPRS wireless receiver are classified and stored, and the optimal acceleration a _h is calculated; and the real-time car parameter information and optimal acceleration a _h are sent back through the GPRS wireless receiver. microcontroller;

(4) The microcontroller controls the car's driving habit optimization module, and uses the car's driving habit optimization module to determine whether there is a gear when the car is driving at this time;

When there is no gear, enter the vehicle speed _Vi at this time and the vehicle speed _Vi+1 in the next second in the car driving habit optimization module; if _Vi = _Vi+1 > 0 more than 5 times, the output idle time has expired Risk warning of long-term carbon deposits;

When there are gears, divide the car speed into N intervals, where N is a positive integer;

In the first interval, judge whether the vehicle speed satisfies: the lower limit of this interval <V _i <V _i+1 ≤ the upper limit of this interval. If it is satisfied, calculate the i-th through a _1i = (V _i+1 -V _i )/t _i The acceleration a _1i within 1s; then further judge whether a _h1 < a _1i is true, where a _h1 is the optimal acceleration in this interval; when it is judged that a _h1 < a _1i is true for 5 consecutive seconds, the risk of carbon deposition when stepping on the accelerator is output warn;

In the second interval, judge whether the vehicle speed satisfies: the upper limit of the first interval <V _i <V _i+1 ≤ the upper limit of this interval. The judgment method is the same as that of the first interval; similarly, the judgment of other intervals is completed;

In the Nth interval, judge whether the vehicle speed satisfies: the upper limit of the previous interval <V _i <V _i+1 ≤ the maximum speed at which the car can safely travel. The judgment method is the same as the first interval;

(5) The microcontroller feeds back the results obtained in step 4) to the cloud database through the GPRS wireless receiver and stores them in the cloud database; if a carbon deposition risk warning appears in step 4), the abnormal data will be transmitted through the Bluetooth module and Bluetooth receiver. Send it to the mobile phone terminal to remind the driver. At the same time, the mobile phone terminal generates an abnormal data report and sends the report to the cloud server through the GPRS wireless receiver and stores it in the cloud database;

(6) Finally, the feedback abnormal data is sorted, counted and analyzed in the cloud database, and driving habit optimization reports are generated for different models and different drivers.

Compared with the prior art, the beneficial effects of the present invention are:

(1) The system can optimize the driver's driving habits, propose effective solutions to bad driving habits, and feed back and record real-time data in the cloud database. Through big data analysis and prediction, different vehicles will be affected by bad driving habits. Various faults caused, as well as the impact of driving habits of different groups of people on the car fault rate, and provide solutions to faults.

(2) The car driving habit optimization module in the system is divided into the idling process and the acceleration process; during the idling process of the car, if the idling time is too long, a carbon deposit risk warning will be issued; during the acceleration process, the car will The optimal acceleration a _h corresponding to the optimal fuel consumption in different speed ranges of the car is used as the threshold. During the acceleration of the car, the acceleration a _i of the car is calculated. By comparing it with a _h , it is concluded whether the optimal acceleration is exceeded. If If the optimal acceleration is exceeded for a long time, the car owner will be warned of the risk of carbon deposits when the accelerator is pressed hard, and timely feedback will be given to the cloud database to generate driving habit optimization reports for different cars and different drivers, reducing failure rates, fuel consumption, and car maintenance costs. .

(3) When calculating the acceleration of a car while driving, the real-time speed input value is the correct value that has been processed and analyzed in the cloud database, reducing the probability of false alarms. The cloud database classifies and organizes car parameter information and real-time data information, extracts the required car data, and sends it to the car driving habit optimization module for calculation. Finally, the feedback results are analyzed and organized to generate driving habit optimization reports for different cars and different drivers.

Description of the drawings

Figure 1 is a schematic block diagram of the overall structure of the system and the connection of an embodiment of the automobile driving style optimization system and optimization method of the present invention; (in the figure: 1. Single chip microcomputer; 2. Automobile OBD data reading module; 3. GPS satellite positioning module; 4. GPRS wireless transmission module; 5. Bluetooth module; 6. Car driving habit optimization module; 7. GPRS wireless receiver; 8. Antenna; 9. Bluetooth receiver; 10. Display; 11. Speaker; 12. Cloud server ; 13. Cloud database; 14. Mobile terminal)

Detailed ways

Specific embodiments of the present invention are given below. The specific examples are only used to further illustrate the present invention and do not limit the scope of protection of the claims of this application.

The invention provides a car driving style optimization system (see Figure 1, referred to as the system), which is characterized in that the system includes a single-chip computer 1, a car OBD data reading module 2, a GPS satellite positioning module 3, a GPRS wireless transmission module 4, and Bluetooth Module 5, car driving habit optimization module 6, GPRS wireless receiver 7, antenna 8, Bluetooth receiver 9, display screen 10, speaker 11, cloud server 12, cloud database 13 and mobile phone terminal 14;

The single-chip microcomputer 1 is connected to the car OBD data reading module 2, the GPS satellite positioning module 3, the GPRS wireless transmission module 4, the Bluetooth module 5 and the car driving habit optimization module 6 respectively; the car OBD data reading module 2 passes through the 16pin interface The line is connected to the car OBD; the GPS satellite positioning module 3 is connected to the antenna 8, and receives satellite signals through the antenna 8; the GPRS wireless transmission module 4 is connected to the GPRS wireless receiver 7, and the data is transmitted to the cloud through the GPRS wireless receiver 7. Server 12; the Bluetooth module 5 is connected to the mobile phone terminal 14 through the Bluetooth receiver 9, and transmits data to the mobile phone terminal 14 through the Bluetooth receiver 9; the cloud server 12 is connected to the GPRS wireless receiver 7 and the cloud database 13 respectively. The server 12 receives the data transmitted by the GPRS wireless receiver 7 and stores the data in the cloud database 13; the car driving habit optimization module 6 is connected to the display screen 10 and the speaker 11 respectively, and controls the display function of the display screen 10 and the speaker 11. Alarm function, and feeds back the data when the alarm occurs to the cloud server 12 and stores it in the cloud database 13 for predicting faults caused by driving behavior.

The model of the microcontroller 1 is STM32F103CBT6.

The car OBD data reading module 2 extracts parameter information during car operation through the car's CAN bus protocol, such as vehicle speed, engine speed, fuel injection volume, relative position of the accelerator pedal, fuel rail pressure and vehicle emissions, etc., as many as 150 items Parameter information.

The GPS satellite positioning module 3 is used for positioning the car, recording the running trajectory of the car and collecting car speed information.

The present invention also provides a method for optimizing automobile driving style (referred to as method), which is characterized by including the following steps:

(1) The single-chip microcomputer 1 controls the car OBD data reading module 2, and extracts the parameter information during car operation through the car's CAN bus protocol, such as vehicle speed, engine speed, fuel injection volume, relative position of the accelerator pedal, fuel rail pressure and vehicle emissions. Up to 150 items of parameter information;

(2) Transmit the parameter information to the cloud server 12 through the GPRS wireless transmission module 4 and the GPRS wireless receiver 7 and store it in the cloud database 13;

(3) In the cloud database 13, the vehicle model and parameter information transmitted by the GPRS wireless receiver 7 is classified and stored, and the optimal acceleration a _h is calculated; and the real-time vehicle speed, engine speed, gear position, fuel injection volume and other parameters are The information and optimal acceleration a _h are sent back to the microcontroller 1 through the GPRS wireless receiver 7;

(4) The single-chip microcomputer 1 controls the car driving habit optimization module 6, and uses the car driving habit optimization module 6 to determine whether there is a gear when the car is driving at this time;

When there is no gear, the vehicle speed _Vi at this time and the vehicle speed _Vi+1 in the next second are input into the car driving habit optimization module 6; if _Vi = _Vi+1 > 0 more than 5 times, the idle time is output Warning about the risk of excessive carbon accumulation;

When there are gears, divide the car speed into N intervals, where N is a positive integer;

In the first interval, judge whether the vehicle speed satisfies: the lower limit of this interval <V _i <V _i+1 ≤ the upper limit of this interval. If it is satisfied, calculate the i-th through a _1i = (V _i+1 -V _i )/t _i The acceleration a _1i within 1s; then further judge whether a _h1 < a _1i is true, where a _h1 is the optimal acceleration in this interval; when it is judged that a _h1 < a _1i is true for 5 consecutive seconds, the risk of carbon deposition when stepping on the accelerator is output warn;

In the second interval, judge whether the vehicle speed satisfies: the upper limit of the first interval <V _i <V _i+1 ≤ the upper limit of this interval. The judgment method is the same as that of the first interval; similarly, the judgment of other intervals is completed;

In the Nth interval, judge whether the vehicle speed satisfies: the upper limit of the previous interval <V _i <V _i+1 ≤ the maximum speed at which the car can safely travel. The judgment method is the same as the first interval;

(5) The single-chip computer 1 feeds back the result obtained in step 4) to the cloud database 13 through the GPRS wireless receiver 7 and stores it in the cloud database 13; if a carbon deposit risk warning occurs in step 4), the result is sent via the Bluetooth module 5 and Bluetooth The receiver 9 sends the abnormal data to the mobile phone terminal 14 to remind the driver. At the same time, the mobile phone terminal 14 generates an abnormal data report and sends the report to the cloud server 12 through the GPRS wireless receiver 7 and stores it in the cloud database 13;

(6) Finally, the feedback abnormal data is sorted, counted and analyzed in the cloud database 13, and a driving habit optimization report is generated for different models and different drivers.

Example 1

A method for optimizing car driving style includes the following steps:

(1) The single-chip microcomputer 1 controls the car OBD data reading module 2, and extracts the parameter information during car operation through the car's CAN bus protocol, such as vehicle speed, engine speed, fuel injection volume, relative position of the accelerator pedal, fuel rail pressure and vehicle emissions. Up to 150 items of parameter information;

(2) Transmit the parameter information to the cloud server 12 through the GPRS wireless transmission module 4 and the GPRS wireless receiver 7 and store it in the cloud database 13;

(3) In the cloud database 13, the vehicle model and parameter information transmitted by the GPRS wireless receiver 7 is classified and stored, and the optimal acceleration a _h is calculated; and the real-time vehicle speed, engine speed, gear position, fuel injection volume and other parameters are The information and optimal acceleration a _h are sent back to the microcontroller 1 through the GPRS wireless receiver 7;

(4) The single-chip microcomputer 1 controls the car driving habit optimization module 6, and uses the car driving habit optimization module 6 to determine whether there is a gear when the car is driving at this time;

When there is no gear, the vehicle speed _Vi at this time and the vehicle speed _Vi+1 in the next second are input into the car driving habit optimization module 6; if _Vi = _Vi+1 > 0 more than 5 times, the idle time is output Warning about the risk of excessive carbon accumulation;

When there is a gear, it is judged whether the vehicle speed is 0<V _i <V _i+1 ≤30, V _i is the vehicle speed at this time, and V _i+1 is the vehicle speed in the next second. If it is satisfied, a _1i = (V _i+1 -V _i )/t _i calculate the acceleration a _1i within the i-th 1s; then further judge whether a _h1 <a _1i is true. When it is judged that a _h1 <a _1i is true for 5 consecutive seconds, the output is to step on the accelerator again. Carbon deposit risk warning;

Determine whether the vehicle speed is 30<V _i <V _i+1 ≤60. If it is satisfied, calculate the acceleration a _2i within the i-th 1s through a _2i = (V _i+1 -V _i )/t _i , and then make further judgments. Whether a _h2 < a _2i is true. When it is judged that a _h2 < a _2i is true for 5 consecutive seconds, a carbon deposit risk warning will be output when the accelerator is pressed heavily;

Determine whether the vehicle speed is 60<V _i <V _i+1 ≤90. If it is satisfied, calculate the acceleration a _3i within the i-th 1s through a _3i = (V _i+1 -V _i )/t _i , and then make further judgments. Whether a _h3 < a _3i is true. When it is judged that a _h2 < a _3i is true for 5 consecutive seconds, a carbon deposit risk warning will be output when the accelerator is pressed heavily;

Determine whether the vehicle speed is 90<V _i <V _i+1 ≤120. If it is satisfied, calculate the acceleration a _i within the i-th 1s through a _4i = (V _i+1 -V _i )/t _i , and then make further judgments. Whether a _h4 < a _4i is true. When it is judged that a _h2 < a _4i is true for 5 consecutive seconds, a carbon deposit risk warning will be output when the accelerator is pressed heavily;

If the judged vehicle speed does not meet the above conditions, the vehicle speed for the next second will continue to be entered, the cycle will continue, and the judgment will be made;

(5) The single-chip computer 1 feeds back the result obtained in step 4) to the cloud database 13 through the GPRS wireless receiver 7 and stores it in the cloud database 13; if a carbon deposit risk warning occurs in step 4), the result is sent via the Bluetooth module 5 and Bluetooth The receiver 9 sends the abnormal data to the mobile phone terminal 14 to remind the driver. At the same time, the mobile phone terminal 14 generates an abnormal data report and sends the report to the cloud server 12 through the GPRS wireless receiver 7 and stores it in the cloud database 13;

(6) Finally, the feedback abnormal data is sorted, counted and analyzed in the cloud database 13 to generate driving habit optimization reports for different models and different drivers.

The parts not described in the present invention are applicable to the existing technology.

Claims (2)

1. The automobile driving mode optimizing method based on the automobile driving mode optimizing system comprises a singlechip, an automobile OBD data reading module, a GPS satellite positioning module, a GPRS wireless transmission module, a Bluetooth module, an automobile driving habit optimizing module, a GPRS wireless receiver, an antenna, a Bluetooth receiver, a display screen, a loudspeaker, a cloud server, a cloud database and a mobile phone terminal;

the singlechip is respectively connected with the automobile OBD data reading module, the GPS satellite positioning module, the GPRS wireless transmission module, the Bluetooth module and the automobile driving habit optimization module; the automobile OBD data reading module is connected with the automobile OBD; the GPS satellite positioning module is connected with the antenna and receives satellite signals through the antenna; the GPRS wireless transmission module is connected with the GPRS wireless receiver; the Bluetooth module is connected with the mobile phone terminal through a Bluetooth receiver; the cloud server is respectively connected with the GPRS wireless receiver and the cloud database; the automobile driving habit optimization module is respectively connected with the display screen and the loudspeaker;

the optimization method is characterized by comprising the following steps of:

(1) The singlechip controls the OBD data reading module of the automobile, and extracts parameter information in the running process of the automobile through a CAN bus protocol of the automobile;

(2) Transmitting the parameter information to a cloud server through a GPRS wireless transmission module and a GPRS wireless receiver and storing the parameter information in a cloud database;

(3) In a cloud database, classifying and storing automobile model and parameter information transmitted by a GPRS wireless receiver, and calculating to obtain optimal acceleration a _h The method comprises the steps of carrying out a first treatment on the surface of the And real-time automobile parameter information and optimal acceleration a _h Sending back to the singlechip through the GPRS wireless receiver;

(4) The singlechip controls the automobile driving habit optimization module, and judges whether a gear exists when the automobile runs at the moment through the automobile driving habit optimization module;

when no gear is present, the current driving habit optimization module is inputVehicle speed V _i And the vehicle speed V of the next second _i+1 The method comprises the steps of carrying out a first treatment on the surface of the If V _i ＝V _i+1 >0 exceeds 5 times, outputting an excessive carbon deposition risk warning for the idle time;

when a gear exists, dividing the speed of the automobile into N sections, wherein N is a positive integer;

in a first section, judging whether the vehicle speed meets the following conditions: the lower limit of this interval<V _i <V _i+1 The upper limit of the interval is less than or equal to the upper limit of the interval, if the upper limit is met, the upper limit is equal to or less than the upper limit of the interval through a _1i ＝(V _i+1 -V _i )/t _i Calculating acceleration a within the ith 1s _1i The method comprises the steps of carrying out a first treatment on the surface of the Further judge a _h1 <a _1i Whether or not to do so, where a _h1 Optimal acceleration in this interval; when judging a continuously for 5s _h1 <a _1i If the two conditions are met, outputting a heavy stepping accelerator carbon deposit risk warning;

in the second interval, judging whether the vehicle speed meets the following conditions: upper limit of the first interval<V _i <V _i+1 The upper limit of the interval is less than or equal to the upper limit of the interval, and the judging method is the same as that of the first interval; the judgment of other intervals is completed in the same way;

in the nth section, it is determined whether the vehicle speed satisfies: upper limit of last interval<V _i <V _i+1 The maximum value of the speed of the safe running of the automobile is less than or equal to the maximum value, and the judging method is the same as that of the first interval;

(5) The singlechip feeds back the result obtained in the step 4) to a cloud database through a GPRS wireless receiver and stores the result in the cloud database; if the carbon deposition risk warning occurs in the step 4), abnormal data are sent to the mobile phone terminal through the Bluetooth module and the Bluetooth receiver to remind a driver, meanwhile, the mobile phone terminal generates an abnormal data report, and the report is sent to the cloud server through the GPRS wireless receiver and stored in the cloud database;

(6) And finally, sorting, counting and analyzing the fed-back abnormal data in the cloud database, and generating driving habit optimization reports for different vehicle types and different drivers.

2. The method for optimizing the driving style of the automobile based on the system for optimizing the driving style of the automobile according to claim 1, wherein the model of the single chip microcomputer is STM32F103CBT6.