CN117783751B - Comprehensive vehicle condition detection system and method for electric vehicle - Google Patents
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Abstract
The invention provides a comprehensive vehicle condition detection system and method of an electric vehicle, and relates to the technical field of electric vehicle quality detection.
Description
Technical Field
The invention relates to the technical field of electric vehicle quality detection, in particular to a comprehensive vehicle condition detection system and method of an electric vehicle.
Background
The electric bicycle is commonly called as a storage battery car, and comprises a plurality of types such as an electric bicycle and an electric tricycle, the electric bicycle or the electric tricycle can be detected before leaving a factory and then sold, but the electric bicycle or the electric tricycle can cause certain damage to a battery and a motor of the electric bicycle due to the problems of transportation, storage and the like in the transportation process, for example, when the motor of the electric bicycle or a circuit node is in a problem, abnormal change of the temperature of the battery and the temperature of the motor can be caused, for example, the motor is in a fault or abnormal operation, additional heat can be caused, the circuit node is in a problem, the node and the battery can generate heat, but the motor works at a lower rotating speed, and the heating value and the power supply current are not matched.
In the prior art, when an electric vehicle is sold, a simple detection is generally performed on the electric vehicle in a simple manner, for example, a voltmeter is used for detecting the voltage of a storage battery, a visual detection mode is used for detecting whether equipment such as a steering lamp and the like normally works, but the part where the electric vehicle is easy to fail is mainly a battery and a motor, the hidden problems of the motor, the battery and the like of the electric vehicle cannot be detected in the prior art, so that hidden trouble hazards are difficult to find in the process of the sales detection, the state of the electric vehicle sold at present cannot be effectively reflected, and in addition, the state of the electric vehicle sold cannot be fed back to a manufacturer in time in the prior art in a manner of being manually detected by the seller, so that the manufacturer is difficult to track the faults in the process of quality assurance and maintenance.
The above information disclosed in the background section is only for enhancement of understanding of the background of the disclosure and therefore it may include information that does not form the prior art that is already known to a person of ordinary skill in the art.
Disclosure of Invention
The invention aims to provide a comprehensive vehicle condition detection system and method for an electric vehicle, which are used for solving the problems in the background technology.
In order to achieve the above purpose, the present invention provides the following technical solutions:
The utility model provides an electric motor car's comprehensive vehicle condition detecting system, includes local detection module, communication module and remote monitoring module, local detection module and communication module electric connection for with the data transmission that detects to communication module, communication module builds the communication network and sends the data of receipt to remote monitoring module, local detection module includes:
The data acquisition module is used for acquiring working data of components in the electric vehicle before and after the working time T of the electric vehicle, and the working data comprise: internal resistance data and voltage data of the battery before and after working, speed curve data of the electric vehicle and power supply current curve data of the battery during working, temperature data of the motor before and after working and temperature data of the battery before and after working;
The data processing module is used for receiving the working data acquired by the data acquisition module, analyzing and processing the temperature data of the motor before and after working, the temperature data of the battery before and after working and the current curve data of the electric vehicle during working to generate a temperature change index, and analyzing and processing the internal resistance data and the voltage data of the battery before and after working and the speed curve data of the electric vehicle during working to generate an electric quantity change index;
The data analysis module is used for carrying out data analysis and processing according to the electric quantity change index and the temperature change index, comprehensively generating an electric vehicle quality index, comparing and analyzing the electric vehicle quality index with a preset abnormal quality reference threshold value, generating a quality grade signal, and transmitting the quality grade signal to the early warning module;
the early warning module receives the quality grade signal and selectively sends out early warning prompts according to the quality grade signal;
The system comprises a data input terminal, a data processing terminal and a data processing terminal, wherein the data input terminal is used for collecting whole vehicle information of the electric vehicle, and the whole vehicle information comprises whole vehicle coding information, whole vehicle specification and model information, dealer information and sales date information;
the communication module is electrically connected with the data input terminal and the data processing module and is used for uploading the whole vehicle information of the electric vehicle collected by the data input terminal and the working data collected by the data collecting module received by the data processing module to the remote monitoring module.
Further, the local detection module further comprises a local communication module, wherein the local communication module is electrically connected with the controller of the electric vehicle and is used for receiving external signals and changing the sign value of a register in the controller of the electric vehicle through the external signals.
Further, collecting working data of components in the electric vehicle before and after the working time T of the electric vehicle, wherein the specific logic is as follows:
Measuring voltage data V 0 of the battery at a time t 0 before working by using a digital multimeter, measuring internal resistance data R 0 of the primary battery by using an alternating current impedance spectrometer, and measuring surface temperature Dt 0 of the battery before working and surface temperature data Mt 0 of the motor;
after the electric vehicle is ridden for a period T, recording speed curve data of the electric vehicle and power supply current curve data of a battery in the period T by using a data acquisition module;
At time T 1 after the riding for T period, the voltage data V 1 of the battery is measured again using the digital multimeter, the internal resistance data R 1 of the primary battery is measured again using the ac impedance spectrometer, and the surface temperature St 1 of the battery and the surface temperature data Mt 1 of the motor after the operation are measured.
Further, the data acquisition module comprises a first controller, and a temperature sensor, a current sensor and a speed sensor which are electrically connected with the first controller, wherein the current sensor is arranged on a power supply loop of a battery of the electric vehicle and is used for measuring power supply current of the battery of the electric vehicle in a test riding T time period, the temperature sensor is provided with two groups which are respectively arranged on the surface of the battery and the surface of a motor and are used for measuring temperature of the surface of the battery of the electric vehicle at the moment T 0 and the moment T 1, the speed sensor is used for measuring speed data in the test riding T time period of the electric vehicle, and the first controller receives and stores the power supply current data of the battery of the electric vehicle, the speed data of the electric vehicle and the temperature data of the battery in the test riding T time period.
Further, the speed curve data of the electric vehicle and the power supply current curve data of the battery in the T time period are discrete point data, the speed sensor is formed based on a Hall effect sensor, the current sensor is formed by adopting the Hall effect sensor, and analog quantity data collected by the speed sensor and the current sensor are subjected to analog-to-digital conversion by a first controller and then are discrete to form the speed curve data and the point data on the power supply current curve of the battery.
Further, the specific calculation formula according to which the data processing module generates the temperature change index is as follows:
Wherein Wdz denotes a temperature change index, α and β are a battery temperature weight and a motor temperature weight, respectively, and 0< α < β, I (T) is current curve data in a time period of test riding of the electric vehicle, and T 0≤t≤t1,t1-t0 =t.
Further, the specific calculation formula according to which the data processing module generates the electric quantity change index is as follows:
wherein Dlz is an electric quantity change index, gamma represents an electric quantity change weight, gamma=0.5 (alpha+beta), and v (T) represents speed curve data in a time period of test riding of the electric vehicle.
Further, a specific calculation formula according to which the data analysis module generates the quality index of the electric vehicle is as follows:
Wherein ZLz represents the quality index of the electric vehicle;
When the quality index of the electric vehicle is compared with a preset abnormal quality reference threshold value to generate a quality grade signal, if the quality index of the electric vehicle is larger than the abnormal quality reference threshold value, a high-influence grade signal is generated and transmitted to an early warning module, an early warning prompt is sent out through the early warning module, and if the quality index of the electric vehicle is smaller than the abnormal quality reference threshold value, a low-influence grade signal is generated and transmitted to the early warning module, and the early warning prompt is not sent out through the early warning module.
Further, the remote monitoring module comprises a remote server and a display terminal, the remote monitoring module receives and stores the data sent by the communication module, and the display terminal is electrically connected with the remote server and is used for reading and displaying the data stored in the remote server.
The invention further provides a comprehensive vehicle condition detection method of the electric vehicle, which is executed by the comprehensive vehicle condition detection system of the electric vehicle and comprises the following steps:
collecting working data of components and parts in the electric motor car around the time of electric motor car work T, the working data includes: internal resistance data and voltage data of the battery before and after working, speed curve data of the electric vehicle and power supply current curve data of the battery during working, temperature data of the motor before and after working and temperature data of the battery before and after working;
Analyzing and processing according to temperature data of the motor before and after working, temperature data of the battery before and after working and current curve data of the electric vehicle during working to generate a temperature change index, and analyzing and processing internal resistance data and voltage data of the battery before and after working and speed curve data of the electric vehicle during working to generate an electric quantity change index;
carrying out data analysis and processing according to the electric quantity change index and the temperature change index, comprehensively generating an electric vehicle quality index, and comparing and analyzing the electric vehicle quality index with a preset abnormal quality reference threshold value to generate a quality grade signal;
Receiving the quality grade signal and selectively sending out an early warning prompt according to the quality grade signal;
The method comprises the steps of collecting whole vehicle information of the electric vehicle, wherein the whole vehicle information comprises whole vehicle coding information, whole vehicle specification and model information, dealer information and sales date information;
And uploading the collected whole vehicle information of the electric vehicle and the collected working data to a remote monitoring terminal of a manufacturer.
Compared with the prior art, the invention has the beneficial effects that:
According to the invention, according to the temperature data of the motor before and after working, the temperature data of the battery before and after working and the current curve data of the electric vehicle during working, a temperature change index is generated, if the motor or the battery works abnormally, the temperature of the motor and the battery generate corresponding abnormality under the condition of outputting certain current, so that the condition of a certain load can be judged through the temperature change index, whether the battery, the motor and the like of the electric vehicle have faults or not can be judged, the analysis is carried out according to the internal resistance data and the voltage data of the battery before and after working and the speed curve data of the electric vehicle during working, the electric quantity change index is generated, the electric vehicle runs for a period of time under the normal state, the battery consumes electricity, the internal resistance is increased and the voltage is reduced, the condition of whether the battery of the electric vehicle has abnormality after the electric vehicle runs for a period of time can be systematically reflected through the electric quantity change index, and the condition of the motor and the battery of the electric vehicle can be systematically reflected through the electric vehicle quality index, so the quality problem of the electric vehicle sold or not, is accurately judged;
The invention also collects the whole vehicle information of the electric vehicle through the data input terminal, and uploads the whole vehicle information and the collected working data of the internal components of the electric vehicle to the remote monitoring module of the factory background through the communication module, and the working data and the whole vehicle information of the electric vehicle during sales can be known timely through the remote monitoring module, so that the factory can conveniently inquire and track faults during after-sales.
Drawings
FIG. 1 is a schematic diagram of the overall system architecture of the present invention;
FIG. 2 is a schematic diagram of the data acquisition structure of the present invention;
FIG. 3 is a flow chart of the detection method of the present invention.
Detailed Description
The present invention will be further described in detail with reference to specific embodiments in order to make the objects, technical solutions and advantages of the present invention more apparent.
It is to be noted that unless otherwise defined, technical or scientific terms used herein should be taken in a general sense as understood by one of ordinary skill in the art to which the present invention belongs. The terms "first," "second," and the like, as used herein, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that elements or items preceding the word are included in the element or item listed after the word and equivalents thereof, but does not exclude other elements or items. The terms "connected" or "connected," and the like, are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. "up", "down", "left", "right" and the like are used only to indicate a relative positional relationship, and when the absolute position of the object to be described is changed, the relative positional relationship may be changed accordingly.
Examples:
referring to fig. 1-2, the present invention provides a technical solution:
the utility model provides a comprehensive vehicle condition detecting system of electric motor car, includes local detection module, communication module and remote monitoring module, local detection module and communication module electric connection for with the data transmission that detects to communication module, communication module builds communication network and sends the data of receiving to remote monitoring module, local detection module includes data acquisition module, data processing module, data analysis module, early warning module and data entry terminal, wherein:
The data acquisition module is used for acquiring working data of components in the electric vehicle before and after the working T time of the electric vehicle, and the working data comprise: internal resistance data and voltage data of the battery before and after working, speed curve data of the electric vehicle and power supply current curve data of the battery during working, temperature data of the motor before and after working and temperature data of the battery before and after working.
In this embodiment, the working data of the components inside the electric vehicle before and after the working T time of the electric vehicle is collected, and the specific logic according to the working data is:
Measuring voltage data V 0 of the battery at a time t 0 before working by using a digital multimeter, measuring internal resistance data R 0 of the primary battery by using an alternating current impedance spectrometer, and measuring surface temperature Dt 0 of the battery before working and surface temperature data Mt 0 of the motor;
after the electric vehicle is ridden for a period T, recording speed curve data of the electric vehicle and power supply current curve data of a battery in the period T by using a data acquisition module;
At time T 1 after the riding for T period, the voltage data V 1 of the battery is measured again using the digital multimeter, the internal resistance data R 1 of the primary battery is measured again using the ac impedance spectrometer, and the surface temperature Dt 1 of the battery and the surface temperature data Mt 1 of the motor after the operation are measured.
In the riding T time period, the electric vehicle inevitably consumes the electric quantity of the battery during normal operation, and the motor normally works, so that the surface temperature can rise along with the operation, when the motor, the battery or a circuit node of the electric vehicle has problems, the output current of the battery can be increased, but in a normal state, certain output current can cause the battery and the motor of the electric vehicle to work in a certain rated state, and if the electric vehicle has faults, the current is not matched with the temperature change of the motor and the battery of the electric vehicle.
Further, the data acquisition module comprises a first controller, and a temperature sensor, a current sensor and a speed sensor which are electrically connected with the first controller, wherein the current sensor is arranged on a power supply loop of a battery of the electric vehicle and is used for measuring power supply current of the battery of the electric vehicle in a test riding T time period, the temperature sensor is provided with two groups which are respectively arranged on the surface of the battery and the surface of a motor and are used for measuring temperature of the surface of the battery of the electric vehicle at the moment T 0 and the moment T 1, the speed sensor is used for measuring speed data in the test riding T time period of the electric vehicle, and the first controller receives and stores the power supply current data of the battery of the electric vehicle, the speed data of the electric vehicle and the temperature data of the battery in the test riding T time period.
The first controller is based on an STM32 embedded development board, the current sensor is a Hall effect current sensor with the model number of ACS712, the temperature sensor is a linear temperature sensor with the model number of LM35, the speed sensor is a Hall effect sensor, the Hall effect sensor for measuring the speed generally comprises a Hall element and a magnetic field source adjacent to the Hall element, the magnetic field source is fixed, the Hall element rotates along with the rotation of a wheel, one side of the Hall element faces the magnetic field, and when the wheel rotates, the magnetic field changes relative to the Hall element, so that the advancing speed of the electric vehicle is measured according to the changing speed.
The first controller comprises a keyboard matrix, wherein rows and columns of the keyboard matrix are respectively connected to general input/output pins of the first controller, each row and each column are ensured to have a unique pin, and data measured by using a digital multimeter and an alternating current impedance spectrometer are manually input into the first controller through the keyboard matrix.
In this embodiment, the speed curve data of the electric vehicle and the power supply current curve data of the battery in the T period are discrete point data, the speed sensor is formed based on a hall effect sensor, the current sensor is formed by using a hall effect sensor, analog quantity data collected by the speed sensor and the current sensor are subjected to analog-to-digital conversion by the first controller and then are discrete to form the speed curve data and the point data on the power supply current curve of the battery, the interval between adjacent points is a sampling interval, and when the sampling interval is shorter, the corresponding speed curve and power supply current curve are formed.
In integrating the speed profile data and the supply current profile, the accumulated speed or current values are used for estimation, allowing the numerical integration to be achieved by simple accumulation.
The data processing module is used for receiving the working data acquired by the data acquisition module, analyzing and processing the temperature data of the motor before and after working, the temperature data of the battery before and after working and the current curve data of the electric vehicle during working to generate a temperature change index, and analyzing and processing the internal resistance data and the voltage data of the battery before and after working and the speed curve data of the electric vehicle during working to generate an electric quantity change index.
Further, the specific calculation formula according to which the data processing module generates the temperature change index is as follows:
Wherein Wdz denotes a temperature change index, α and β are a battery temperature weight and a motor temperature weight, respectively, and 0< α < β, I (T) is current curve data in a time period of test riding of the electric vehicle, and T 0≤t≤t1,t1-t0 =t.
When the difference between the battery temperature and the motor temperature before and after the test riding T time period is higher, the larger the temperature change index is, the more abnormal heat is possibly caused by faults, when the integral of the power supply current curve over time is larger in the test riding T time period, the smaller the temperature change index is, because the larger the integral of the power supply current curve over time is, the larger the battery load is, namely the higher the power of the motor is, the higher the heating value of the battery is, the higher the heating value of the motor is, the temperature change index is relatively smaller, when the integral of the power supply current curve over time is smaller, the larger the temperature change index is, the larger the current is used for generating heat, and the abnormal heat generating point is possibly caused by faults.
Further, the specific calculation formula according to which the data processing module generates the electric quantity change index is as follows:
wherein Dlz is an electric quantity change index, gamma represents an electric quantity change weight, gamma=0.5 (alpha+beta), and v (T) represents speed curve data in a time period of test riding of the electric vehicle.
With the riding of the electric vehicle, the electric quantity of the battery is consumed, at this moment, the internal resistance of the battery is increased, the voltage is reduced, when the internal resistance of the battery is changed before and after the T period of the test riding and the voltage drop of the battery are higher, the larger the electric quantity change index is, which indicates that abnormal electricity consumption possibly exists, when the integral of the speed curve with respect to time is larger in the T period of the test riding, the smaller the electric quantity change index is, because the integral of the power supply current curve with respect to time is larger, the larger the distance of the riding is, namely the longer the running time of the motor is, the higher the electric quantity of the battery is, the smaller the electric quantity change index is, when the integral of the speed curve with respect to time is smaller, namely the distance of the riding is shorter, at this moment, the internal resistance of the battery is changed before and after the T period of the test riding and the voltage drop of the battery is higher, which indicates that a large amount of electric energy is abnormally consumed, at this moment, which indicates that abnormal electricity consumption exists, and the motor and the battery possibly has faults.
The data analysis module is used for carrying out data analysis and processing according to the electric quantity change index and the temperature change index, comprehensively generating an electric vehicle quality index, comparing and analyzing the electric vehicle quality index with a preset abnormal quality reference threshold value, generating a quality grade signal, and transmitting the quality grade signal to the early warning module.
In this embodiment, a specific calculation formula according to which the data analysis module generates the quality index of the electric vehicle is:
Wherein ZLz represents the quality index of the electric vehicle.
In the present embodiment of the present invention,Representing the reciprocal of the average velocity,/>The inverse of the average power supply current is indicated, so that the higher the average riding speed is, the higher the power of the motor in unit time generates higher heat, the lower the quality index of the electric vehicle is, the higher the average power supply current is, the higher the power of the motor is, the higher the consumed electric energy is, the lower the quality index of the electric vehicle is, the higher the quality index of the electric vehicle is, and the inverse of the average riding speed and the average power supply current is adopted to further correct the quality index of the electric vehicle, so that the error is reduced.
When the quality index of the electric vehicle is compared with a preset abnormal quality reference threshold value to generate a quality grade signal, if the quality index of the electric vehicle is larger than the abnormal quality reference threshold value, a high-influence grade signal is generated and transmitted to an early warning module, an early warning prompt is sent out through the early warning module, and if the quality index of the electric vehicle is smaller than the abnormal quality reference threshold value, a low-influence grade signal is generated and transmitted to the early warning module, and the early warning prompt is not sent out through the early warning module.
The early warning module receives the quality grade signal and selectively sends out early warning prompt according to the quality grade signal, the data analysis module is also based on an STM32 embedded development board, the early warning module can adopt signal reminding devices such as a loudspeaker and a warning lamp, compares the quality index of the electric vehicle with a preset quality reference threshold value, and controls the corresponding early warning module to work according to a control result.
The data input terminal is used for collecting the whole car information of the electric car, the whole car information comprises whole car coding information, whole car specification and model information, distributor information and sales date information, and the data input terminal can adopt terminals such as a PC (personal computer), a mobile phone and the like and is used for inputting the whole car information.
The communication module is electrically connected with the data input terminal and the data processing module and is used for uploading the whole vehicle information of the electric vehicle collected by the data input terminal and the working data collected by the data collecting module received by the data processing module to the remote monitoring module, and the communication module adopts a Ai Moxun model SX1278 wireless communication module and sends the received data to the inside of the remote monitoring module with the appointed IP.
The remote monitoring module comprises a remote server and a display terminal, the remote monitoring module receives and stores data sent by the communication module, the display terminal is electrically connected with the remote server and is used for reading and displaying the data stored in the remote server, the remote server is provided with a unique IP, the data sent by the communication module is received, the display terminal internally comprises an operating system, a display screen and the like, and the display is performed by reading parameters in the remote server.
The local detection module further comprises a local communication module, the local communication module is electrically connected with the controller of the electric vehicle and is used for receiving external signals, the sign value of the register in the controller of the electric vehicle is changed through the external signals, the local communication module comprises a Bluetooth module, an input/output interface and the like, can receive data of an external terminal and is equivalent to downloading of a program, and the sign value of the register in the controller of the electric vehicle is modified, so that the technical effects of speed limiting removal and the like can be achieved.
Referring to fig. 3, the present invention further provides a method for detecting a comprehensive vehicle condition of an electric vehicle, where the method is executed by the above-mentioned system for detecting a comprehensive vehicle condition of an electric vehicle, and includes:
collecting working data of components and parts in the electric motor car around the time of electric motor car work T, the working data includes: internal resistance data and voltage data of the battery before and after working, speed curve data of the electric vehicle and power supply current curve data of the battery during working, temperature data of the motor before and after working and temperature data of the battery before and after working;
Analyzing and processing according to temperature data of the motor before and after working, temperature data of the battery before and after working and current curve data of the electric vehicle during working to generate a temperature change index, and analyzing and processing internal resistance data and voltage data of the battery before and after working and speed curve data of the electric vehicle during working to generate an electric quantity change index;
carrying out data analysis and processing according to the electric quantity change index and the temperature change index, comprehensively generating an electric vehicle quality index, and comparing and analyzing the electric vehicle quality index with a preset abnormal quality reference threshold value to generate a quality grade signal;
Receiving the quality grade signal and selectively sending out an early warning prompt according to the quality grade signal;
The method comprises the steps of collecting whole vehicle information of the electric vehicle, wherein the whole vehicle information comprises whole vehicle coding information, whole vehicle specification and model information, dealer information and sales date information;
And uploading the collected whole vehicle information of the electric vehicle and the collected working data to a remote monitoring terminal of a manufacturer.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. Those of skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application.
Claims (5)
1. The utility model provides a comprehensive vehicle condition detecting system of electric motor car, its characterized in that includes local detection module, communication module and remote monitoring module, local detection module and communication module electric connection for with the data transmission that detects to communication module, communication module builds the communication network and sends the data of receipt to remote monitoring module, local detection module includes:
the data acquisition module is used for acquiring the work of the electric vehicle Before and after the time, the working data of the components in the electric vehicle comprises: internal resistance data and voltage data of the battery before and after working, speed curve data of the electric vehicle and power supply current curve data of the battery during working, temperature data of the motor before and after working and temperature data of the battery before and after working;
The data processing module is used for receiving the working data acquired by the data acquisition module, analyzing and processing the temperature data of the motor before and after working, the temperature data of the battery before and after working and the current curve data of the electric vehicle during working to generate a temperature change index, and analyzing and processing the internal resistance data and the voltage data of the battery before and after working and the speed curve data of the electric vehicle during working to generate an electric quantity change index;
The data analysis module is used for carrying out data analysis and processing according to the electric quantity change index and the temperature change index, comprehensively generating an electric vehicle quality index, comparing and analyzing the electric vehicle quality index with a preset abnormal quality reference threshold value, generating a quality grade signal, and transmitting the quality grade signal to the early warning module;
the early warning module receives the quality grade signal and selectively sends out early warning prompts according to the quality grade signal;
The system comprises a data input terminal, a data processing terminal and a data processing terminal, wherein the data input terminal is used for collecting whole vehicle information of the electric vehicle, and the whole vehicle information comprises whole vehicle coding information, whole vehicle specification and model information, dealer information and sales date information;
The communication module is electrically connected with the data input terminal and the data processing module and is used for uploading the whole vehicle information of the electric vehicle collected by the data input terminal and the working data collected by the data collecting module received by the data processing module to the remote monitoring module;
The local detection module further comprises a local communication module, the local communication module is electrically connected with the controller of the electric vehicle and used for receiving external signals, changing the sign value of a register in the controller of the electric vehicle through the external signals and collecting the work of the electric vehicle Working data of components in the electric vehicle before and after time are as follows:
Before working Measurement of voltage data of a battery using a digital multimeter at timeMeasuring internal resistance data/>, of primary battery using an ac impedance spectrometerMeasuring surface temperature of cell before operation/>And surface temperature data of the motor/>；
Test riding of electric vehicleAfter a period of time, record/>, using a data acquisition moduleSpeed curve data of the electric vehicle and power supply current curve data of the battery in the time period;
Riding />, After a period of timeAt time, the voltage data/>, of the battery was measured again using a digital multimeterAnd measuring the internal resistance data/>, of the primary battery again using an ac impedance spectrometerAnd measuring the surface temperature/>, of the battery after operationAnd surface temperature data of the motor/>；
The specific calculation formula according to which the data processing module generates the temperature change index is as follows:
，
Wherein, Indicating the temperature change index,/>、/>Battery temperature weight and motor temperature weight, respectively, and，/>For electric vehicle riding test/>Current profile data over a time period, and/>，/>；
The specific calculation formula according to which the data processing module generates the electric quantity change index is as follows:
，
Wherein, Is the index of change of electric quantity,/>Represents the power change weight, and/>，/>Represents the riding trial of the electric vehicle/>Speed profile data over a time period;
The specific calculation formula according to which the data analysis module generates the quality index of the electric vehicle is as follows:
，
Wherein, Representing the quality index of the electric vehicle;
When the quality index of the electric vehicle is compared with a preset abnormal quality reference threshold value to generate a quality grade signal, if the quality index of the electric vehicle is larger than the abnormal quality reference threshold value, a high-influence grade signal is generated and transmitted to an early warning module, an early warning prompt is sent out through the early warning module, and if the quality index of the electric vehicle is smaller than the abnormal quality reference threshold value, a low-influence grade signal is generated and transmitted to the early warning module, and the early warning prompt is not sent out through the early warning module.
2. The integrated vehicle condition detection system of an electric vehicle of claim 1, wherein: the data acquisition module comprises a first controller, and a temperature sensor, a current sensor and a speed sensor which are electrically connected with the first controller, wherein the current sensor is arranged on a power supply circuit of an electric vehicle battery and is used for measuring the test riding of the electric vehicleIn the time period, the temperature sensors are provided with two groups, are respectively arranged on the surface of the battery and the surface of the motor and are used for measuring/>Time of day and/>The temperature of the battery surface of the electric vehicle at the moment, and the speed sensor is used for measuring the riding trial/>The first controller receives and stores speed data over a period of time, the first controller receives and stores electric vehicle test ride/>In the time period, power supply current data of a battery of the electric vehicle, speed data of the electric vehicle and temperature data of the battery.
3. The integrated vehicle condition detection system of an electric vehicle of claim 2, wherein: the saidThe speed curve data of the electric vehicle and the power supply current curve data of the battery in the time period are discrete point data, the speed sensor is formed based on a Hall effect sensor, the current sensor is formed by adopting the Hall effect sensor, and analog quantity data collected by the speed sensor and the current sensor are subjected to analog-to-digital conversion by a first controller and then are discrete to form the speed curve data and the point data on the power supply current curve of the battery.
4. The integrated vehicle condition detection system of an electric vehicle of claim 1, wherein: the remote monitoring module comprises a remote server and a display terminal, the remote monitoring module receives and stores the data sent by the communication module, and the display terminal is electrically connected with the remote server and is used for reading and displaying the data stored in the remote server.
5. A comprehensive vehicle condition detection method of an electric vehicle is characterized in that: the detection method is performed by the integrated vehicle condition detection system of the electric vehicle according to any one of claims 1 to 4, comprising:
Collecting work of electric vehicle Before and after the time, the working data of the components in the electric vehicle comprises: internal resistance data and voltage data of the battery before and after working, speed curve data of the electric vehicle and power supply current curve data of the battery during working, temperature data of the motor before and after working and temperature data of the battery before and after working;
Analyzing and processing according to temperature data of the motor before and after working, temperature data of the battery before and after working and current curve data of the electric vehicle during working to generate a temperature change index, and analyzing and processing internal resistance data and voltage data of the battery before and after working and speed curve data of the electric vehicle during working to generate an electric quantity change index;
carrying out data analysis and processing according to the electric quantity change index and the temperature change index, comprehensively generating an electric vehicle quality index, and comparing and analyzing the electric vehicle quality index with a preset abnormal quality reference threshold value to generate a quality grade signal;
Receiving the quality grade signal and selectively sending out an early warning prompt according to the quality grade signal;
The method comprises the steps of collecting whole vehicle information of the electric vehicle, wherein the whole vehicle information comprises whole vehicle coding information, whole vehicle specification and model information, dealer information and sales date information;
And uploading the collected whole vehicle information of the electric vehicle and the collected working data to a remote monitoring terminal of a manufacturer.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110515005A (en) * | 2019-08-13 | 2019-11-29 | 上海欣诣科技有限公司 | A kind of spontaneous combustion early warning system for the electric car in charging pile monitoring charging |
| CN114889433A (en) * | 2022-04-29 | 2022-08-12 | 奇瑞新能源汽车股份有限公司 | Thermal runaway alarm system and method for battery of electric vehicle |
| CN115130266A (en) * | 2021-03-24 | 2022-09-30 | 纬湃科技投资(中国)有限公司 | Method and system for thermal management control of a vehicle |
| CN115661975A (en) * | 2022-10-13 | 2023-01-31 | 江西五十铃汽车有限公司 | Vehicle condition data acquisition method, system, storage medium and equipment |
| CN115840437A (en) * | 2022-12-14 | 2023-03-24 | 无锡四海电子科技有限公司 | Fault detection method and system for new energy power supply controller |
-
2023
- 2023-12-29 CN CN202311853582.3A patent/CN117783751B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110515005A (en) * | 2019-08-13 | 2019-11-29 | 上海欣诣科技有限公司 | A kind of spontaneous combustion early warning system for the electric car in charging pile monitoring charging |
| CN115130266A (en) * | 2021-03-24 | 2022-09-30 | 纬湃科技投资(中国)有限公司 | Method and system for thermal management control of a vehicle |
| CN114889433A (en) * | 2022-04-29 | 2022-08-12 | 奇瑞新能源汽车股份有限公司 | Thermal runaway alarm system and method for battery of electric vehicle |
| CN115661975A (en) * | 2022-10-13 | 2023-01-31 | 江西五十铃汽车有限公司 | Vehicle condition data acquisition method, system, storage medium and equipment |
| CN115840437A (en) * | 2022-12-14 | 2023-03-24 | 无锡四海电子科技有限公司 | Fault detection method and system for new energy power supply controller |
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