CN114500504A - Intelligent early warning method for motor efficiency deterioration, computer storage medium and vehicle - Google Patents
Intelligent early warning method for motor efficiency deterioration, computer storage medium and vehicle Download PDFInfo
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- CN114500504A CN114500504A CN202210061689.3A CN202210061689A CN114500504A CN 114500504 A CN114500504 A CN 114500504A CN 202210061689 A CN202210061689 A CN 202210061689A CN 114500504 A CN114500504 A CN 114500504A
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- 230000006866 deterioration Effects 0.000 title claims abstract description 35
- 238000000034 method Methods 0.000 title claims abstract description 27
- 238000005457 optimization Methods 0.000 claims abstract description 22
- 238000004590 computer program Methods 0.000 claims description 5
- 239000000446 fuel Substances 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 229910052739 hydrogen Inorganic materials 0.000 description 1
- 239000001257 hydrogen Substances 0.000 description 1
- 230000002452 interceptive effect Effects 0.000 description 1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/06—Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L3/00—Electric devices on electrically-propelled vehicles for safety purposes; Monitoring operating variables, e.g. speed, deceleration or energy consumption
- B60L3/0023—Detecting, eliminating, remedying or compensating for drive train abnormalities, e.g. failures within the drive train
- B60L3/0061—Detecting, eliminating, remedying or compensating for drive train abnormalities, e.g. failures within the drive train relating to electrical machines
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- B60Q9/00—Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00, e.g. haptic signalling
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0808—Diagnosing performance data
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
- G08B21/185—Electrical failure alarms
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- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mechanical Engineering (AREA)
- Physics & Mathematics (AREA)
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- Computer Networks & Wireless Communication (AREA)
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Abstract
The invention relates to an intelligent early warning method for motor efficiency deterioration, a computer storage medium and a vehicle, relating to the technical field of vehicle intelligent early warning, and comprising the steps of acquiring vehicle data, uploading the data to a big data cloud platform in real time, calculating motor efficiency distribution in a certain working period by the big data cloud platform, and judging whether the usage proportion of a motor high-efficiency area is less than 90%; if the usage ratio of the motor high-efficiency area is more than or equal to 90%, returning to the previous step again; if the usage proportion of the motor high-efficiency area is less than 90%, the big data cloud platform sends out motor efficiency deterioration early warning prompts to a user, and the user determines whether to optimize according to the usage condition; judging whether to execute optimization; if the optimization is executed, executing the optimization execution through the big data cloud platform; and if the optimization is not executed, stopping early warning. The advantages are that: the motor efficiency deterioration problem can be found in time by a user, and optimization can be performed in time aiming at the problem so as to ensure that the vehicle always runs in the optimal state.
Description
Technical Field
The invention relates to the technical field of intelligent early warning of vehicles, in particular to an intelligent early warning method for motor efficiency deterioration, a computer storage medium and a vehicle.
Background
The new energy automobile adopts unconventional automobile fuel as a power source (or adopts conventional automobile fuel and a novel vehicle-mounted power device), integrates advanced technologies in the aspects of power control and driving of the automobile, and forms an automobile with advanced technical principle, new technology and new structure; the new energy automobile comprises a pure electric automobile, an extended range electric automobile, a hybrid electric automobile, a fuel cell electric automobile, a hydrogen engine automobile and the like.
With the rapid development of economy in China, the pressure of energy safety and energy conservation and environmental protection is increasing day by day, and the popularization and popularization of new energy automobiles become the important strategic direction of China.
At present, after the pure electric vehicle motor is used for many years, the efficiency is deteriorated, and the endurance mileage of the whole vehicle is reduced. The prior art center has no related early warning prompt of motor efficiency deterioration, so that a user does not know the reason for reducing the endurance mileage, and the user experience is influenced.
The foregoing description is provided for general background information and is not admitted to be prior art.
Disclosure of Invention
The invention aims to provide an intelligent early warning method for motor efficiency deterioration, a computer storage medium and a vehicle.
The invention provides a virtual scene interactive voice HRTF positioning method, which comprises the following steps:
s1: acquiring finished automobile data, and entering the step S2;
s2: uploading data to a big data cloud platform in real time, and entering the step S3;
s3: the big data cloud platform calculates the motor efficiency distribution in a certain working period, and then the step S4 is carried out;
s4: judging whether the usage proportion of the high-efficiency area of the motor is less than 90%;
if the usage ratio of the motor high-efficiency area is more than or equal to 90%, returning to the step S3 again;
if the usage ratio of the motor high-efficiency area is less than 90%, the step S5 is carried out;
s5: the big data cloud platform sends out a motor efficiency deterioration early warning prompt to a user, and the step S6 is carried out;
s6: the user determines whether to optimize according to the use condition and enters the step S7;
s7: judging whether to execute optimization;
if the optimization is executed, executing the optimization execution through the big data cloud platform, and returning to the step S2 again;
and if the optimization is not executed, stopping early warning.
Further, the vehicle data in the step S1 includes bus voltage at two ends of the motor, bus current at two ends of the motor, motor speed, and motor torque.
Further, the step of S3 includes:
s31: calculating the motor efficiency according to the whole vehicle data and the formula (1) and the formula (2);
s32: dividing the motor efficiency distribution into three parts of a high-efficiency area ratio, a medium-efficiency area ratio and a low-efficiency area ratio, and calculating the motor efficiency distribution ratio.
Further, the formula in the step S3 is:
further, η in the formula (1) and the formula (2) represents motor efficiency, U represents bus voltage across the motor, I represents bus current across the motor, n represents motor rotation speed, and T represents motor torque.
The invention also provides a computer storage medium, which comprises a computer program, and when the computer program is executed, the intelligent early warning method for the motor efficiency deterioration is executed to load the early warning method.
The invention also provides a vehicle, and the vehicle adopts the intelligent early warning method for the motor efficiency deterioration to carry out early warning on the motor efficiency deterioration of the vehicle.
According to the intelligent early warning method for the motor efficiency deterioration, the motor efficiency is analyzed according to the power system data uploaded to the big data cloud platform by the whole vehicle, so that whether the motor is aged or not and whether the efficiency is reduced or not are judged; the motor efficiency is monitored through the whole vehicle data uploaded to the big data cloud platform, if the efficiency of the motor becomes low after the motor is used for many years, a system sends a prompt to a user, and optimization is carried out according to the user prompt so as to continuously keep the whole vehicle running in an optimal state and avoid the problem that the user experience is influenced by the low motor efficiency; the motor efficiency deterioration problem can be found in time by a user, and optimization can be performed in time aiming at the problem, so that the vehicle can be ensured to always operate in the optimal state.
Drawings
Fig. 1 is a flowchart of an intelligent warning method for motor efficiency deterioration according to an embodiment of the present invention.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
The terms first, second, third, fourth and the like in the description and in the claims of the present invention are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order.
Example 1
Fig. 1 is a flowchart of an intelligent warning method for motor efficiency deterioration according to an embodiment of the present invention. Referring to fig. 1, the intelligent early warning method for motor efficiency deterioration provided by the embodiment of the invention includes the following steps:
s1: acquiring finished automobile data, and entering the step S2;
s2: uploading data to a big data cloud platform in real time, and entering the step S3;
s3: the big data cloud platform calculates the motor efficiency distribution in a certain working period, and then the step S4 is carried out;
s4: judging whether the usage proportion of the high-efficiency area of the motor is less than 90%;
if the usage ratio of the motor high-efficiency area is more than or equal to 90%, returning to the step S3 again;
if the usage ratio of the motor high-efficiency area is less than 90%, the step S5 is carried out;
s5: the big data cloud platform sends out a motor efficiency deterioration early warning prompt to a user, and the step S6 is carried out;
s6: the user determines whether to optimize according to the use condition and enters the step S7;
s7: judging whether to execute optimization;
if the optimization is executed, executing the optimization execution through the big data cloud platform, and returning to the step S2 again;
and if the optimization is not executed, stopping early warning.
The intelligent early warning method for the motor efficiency deterioration provided by the invention analyzes the motor efficiency according to the power system data transmitted to the big data cloud platform on the whole vehicle, so as to judge whether the motor is aged or not and whether the efficiency is reduced or not; the motor efficiency is monitored through the whole vehicle data uploaded to the big data cloud platform, if the efficiency of the motor becomes low after the motor is used for many years, a system sends a prompt to a user, and optimization is carried out according to the user prompt so as to continuously keep the whole vehicle running in an optimal state and avoid the problem that the user experience is influenced by the low motor efficiency; the motor efficiency deterioration problem can be found in time by a user, and optimization can be performed in time aiming at the problem so as to ensure that the vehicle always runs in the optimal state.
Specifically, the vehicle data in the step S1 includes bus voltage at two ends of the motor, bus current at two ends of the motor, motor speed, and motor torque. The step of S3 includes:
s31: calculating the motor efficiency according to the whole vehicle data and the formula (1) and the formula (2);
s32: dividing the motor efficiency distribution into three parts of a high-efficiency area ratio, a medium-efficiency area ratio and a low-efficiency area ratio, and calculating the motor efficiency distribution ratio.
The formula in step S3 is:
further, η in the formula (1) and the formula (2) represents motor efficiency, U represents bus voltage across the motor, I represents bus current across the motor, n represents motor rotation speed, and T represents motor torque.
The embodiment of the invention also provides a computer storage medium, which comprises a computer program, and when the computer program is executed, the intelligent early warning method for the motor efficiency deterioration is executed to load the early warning method.
The embodiment of the invention also provides a vehicle, and the vehicle adopts the intelligent early warning method for the motor efficiency deterioration to carry out early warning on the motor efficiency deterioration of the vehicle. For other technical features of the vehicle, please refer to the prior art, which is not described herein.
Based on the above description, the present invention has the following advantages:
1. according to the intelligent early warning method for the motor efficiency deterioration, the motor efficiency is analyzed according to the power system data uploaded to the big data cloud platform by the whole vehicle, so that whether the motor is aged or not and whether the efficiency is reduced or not are judged; the motor efficiency is monitored through the whole vehicle data uploaded to the big data cloud platform, if the motor becomes low in efficiency after being used for many years, the system sends a prompt to a user, and optimization is carried out according to the user prompt, so that the whole vehicle can be continuously kept in the best running state, and the problem that the motor efficiency becomes low to influence the user experience is avoided.
2. The intelligent early warning method for the motor efficiency deterioration provided by the invention enables a user to find the problem of the motor efficiency deterioration in time and optimize the problem in time so as to ensure that a vehicle always runs in an optimal state.
The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.
Claims (7)
1. An intelligent early warning method for motor efficiency deterioration is characterized by comprising the following steps:
s1: acquiring finished automobile data, and entering the step S2;
s2: uploading data to a big data cloud platform in real time, and entering the step S3;
s3: the big data cloud platform calculates the motor efficiency distribution in a certain working period, and then the step S4 is carried out;
s4: judging whether the usage proportion of the motor high-efficiency area is less than 90%;
if the usage ratio of the motor high-efficiency area is more than or equal to 90%, returning to the step S3 again;
if the usage ratio of the motor high-efficiency area is less than 90%, the step S5 is carried out;
s5: the big data cloud platform sends out a motor efficiency deterioration early warning prompt to a user, and the step S6 is carried out;
s6: the user determines whether to optimize according to the use condition and enters the step S7;
s7: judging whether to execute optimization;
if the optimization is executed, executing the optimization execution through the big data cloud platform, and returning to the step S2 again;
and if the optimization is not executed, stopping early warning.
2. The intelligent early warning method for motor efficiency deterioration according to claim 1, wherein the vehicle data in the step S1 includes bus voltage across the motor, bus current across the motor, motor speed, and motor torque.
3. The intelligent warning method for motor efficiency deterioration according to claim 2, wherein the S3 step includes:
s31: calculating the motor efficiency according to the whole vehicle data and the formula (1) and the formula (2);
s32: dividing the motor efficiency distribution into three parts of a high-efficiency area ratio, a medium-efficiency area ratio and a low-efficiency area ratio, and calculating the motor efficiency distribution ratio.
4. The intelligent warning method for motor efficiency deterioration according to claim 3, wherein the formula in the step S3 is as follows:
5. the intelligent warning method for motor efficiency deterioration according to claim 4, wherein η in the formula (1) and the formula (2) represents motor efficiency, U represents bus voltage across the motor, I represents bus current across the motor, n represents motor speed, and T represents motor torque.
6. A computer storage medium comprising a computer program that, when executed, loads a warning method by performing the intelligent warning method of deterioration of motor efficiency of any one of claims 1 to 5.
7. A vehicle, characterized in that the vehicle adopts the intelligent early warning method for the efficiency deterioration of the motor of the vehicle as claimed in any one of claims 1 to 5 to early warn the efficiency deterioration of the motor of the vehicle.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202210061689.3A CN114500504A (en) | 2022-01-19 | 2022-01-19 | Intelligent early warning method for motor efficiency deterioration, computer storage medium and vehicle |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202210061689.3A CN114500504A (en) | 2022-01-19 | 2022-01-19 | Intelligent early warning method for motor efficiency deterioration, computer storage medium and vehicle |
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102969970A (en) * | 2012-12-11 | 2013-03-13 | 常州工学院 | Motor efficiency tracking driving system and driving method |
| CN108583583A (en) * | 2018-03-29 | 2018-09-28 | 科力远混合动力技术有限公司 | Battery Management System for Hybrid Electric Vehicle communication failure judges and processing method |
| CN109177734A (en) * | 2018-08-31 | 2019-01-11 | 南京越博电驱动系统有限公司 | A kind of pure electric automobile motor working efficiency monitoring system and its monitoring method |
| WO2021073036A1 (en) * | 2019-10-15 | 2021-04-22 | 江苏大学 | Real-time global optimization intelligent control system and method for fuel cell bus |
| CN113902233A (en) * | 2020-06-22 | 2022-01-07 | 比亚迪股份有限公司 | Vehicle safety early warning method, big data platform device, vehicle-mounted terminal and vehicle |
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- 2022-01-19 CN CN202210061689.3A patent/CN114500504A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102969970A (en) * | 2012-12-11 | 2013-03-13 | 常州工学院 | Motor efficiency tracking driving system and driving method |
| CN108583583A (en) * | 2018-03-29 | 2018-09-28 | 科力远混合动力技术有限公司 | Battery Management System for Hybrid Electric Vehicle communication failure judges and processing method |
| CN109177734A (en) * | 2018-08-31 | 2019-01-11 | 南京越博电驱动系统有限公司 | A kind of pure electric automobile motor working efficiency monitoring system and its monitoring method |
| WO2021073036A1 (en) * | 2019-10-15 | 2021-04-22 | 江苏大学 | Real-time global optimization intelligent control system and method for fuel cell bus |
| CN113902233A (en) * | 2020-06-22 | 2022-01-07 | 比亚迪股份有限公司 | Vehicle safety early warning method, big data platform device, vehicle-mounted terminal and vehicle |
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Address after: Room 208, Floor 2, Building 3, No. 168, Shennan Road, Minhang District, Shanghai, 201108 Applicant after: Bureton Technology Co.,Ltd. Address before: 201100 room g68, 3 / F, building 6, 4299 Jindu Road, Minhang District, Shanghai Applicant before: Burleton Technology Co.,Ltd. |
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| CB02 | Change of applicant information | ||
| CB03 | Change of inventor or designer information |
Inventor after: Sun Yongbin Inventor after: Chen Fangming Inventor after: Liu Jishun Inventor after: Jiang Lei Inventor after: Meng Weixiang Inventor after: Yan Aolang Inventor before: Sun Yongbin Inventor before: Chen Fangming Inventor before: Liu Jishun Inventor before: Jiang Lei Inventor before: Meng Weixiang Inventor before: Yan Aolang |
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