Electric tricycle motor diagnosis device and diagnosis method
Patent Information
- Application Number
- CN202511670493.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-14
- Publication Date
- 2026-01-27
Smart Images

Figure CN121409334A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of motor diagnostic technology, specifically relating to a diagnostic device and method for an electric tricycle motor. Background Technology
[0002] Electric tricycles are widely used in urban and rural areas of my country as an important short-distance transportation and passenger-carrying tool. The reliability and safety of their drive motors are directly related to the vehicle's operating efficiency and the personal and property safety of users. Under conditions such as long-term high-load operation, internal bearing wear, coil insulation aging, or harsh external environment, the motor is prone to malfunctions such as overheating and abnormal vibration. If not detected and dealt with in time, minor faults may develop into motor burnout, vehicle breakdown, or even safety accidents, causing significant economic losses.
[0003] Currently, when using electric tricycles, users mostly maintain the motor through daily observation or periodic inspection. Users cannot observe the motor's status in real time during use. They usually only deal with it when the motor makes obvious abnormal noises, emits smoke, or its performance deteriorates significantly. By then, the motor has often suffered irreversible damage, making it inconvenient for people to use. Summary of the Invention
[0004] The purpose of this invention is to provide a simple and reasonably designed diagnostic device and method for electric tricycle motors in order to solve the above-mentioned problems.
[0005] The present invention achieves the above objectives through the following technical solutions: A diagnostic device and method for an electric tricycle motor, comprising a motor, and further comprising: A vibration detection module, comprising a vibration sensor fixedly mounted on the top housing of the motor; A temperature monitoring module is mounted on the outside of the motor housing via a fixing mechanism; The temperature monitoring module includes a first arc-shaped plate and a second arc-shaped plate that can surround the motor housing. Fixing plates are installed on the inner sidewalls of the first arc-shaped plate and the second arc-shaped plate. High-precision patch thermocouples that fit tightly against the outer housing of the motor are installed on the side of the two fixing plates closest to the motor.
[0006] As a further optimization of the present invention, the first arc-shaped plate and the second arc-shaped plate are fixedly connected by at least one set of connecting components. The connecting components include a first mounting plate and a second mounting plate respectively fixed on the first arc-shaped plate and the second arc-shaped plate. The first mounting plate and the second mounting plate are respectively provided with a plurality of corresponding first mounting holes and second mounting holes. The bolt passes through the corresponding first mounting holes and second mounting holes and is locked by a nut.
[0007] As a further optimization of the present invention, the first arc-shaped plate, the second arc-shaped plate, and the fixing plate are all made of high thermal conductivity material.
[0008] A diagnostic method for an electric tricycle motor includes the following steps: S1. Data acquisition: Real-time temperature data of the motor is acquired using the high-precision patch thermocouple, and real-time vibration data of the motor is acquired using the vibration sensor. S2. Data Analysis: The collected temperature and vibration data are uploaded to the data processing module. The data processing module compares the real-time temperature value with the preset temperature threshold and classifies it into three levels: T1, T2, and T3. At the same time, the data processing module calculates the root mean square value of the vibration data and compares the root mean square value with the preset vibration threshold and classifies it into three levels: V1, V2, and V3. S3, Data Transmission and Display Module: The data transmission module transmits the analyzed temperature level, vibration level and their corresponding values to the human-machine interaction module for real-time display. S4. Status Warning and Alarm Module: The human-machine interaction module performs the following operations based on the received level information: When the temperature display shows T2 or the vibration display shows V2, an audible and visual warning will be triggered to alert the user and prompt timely maintenance. When the temperature display shows T3 or the vibration display shows V3, a strong alarm will be triggered, and it is recommended to stop the vehicle immediately.
[0009] As a further optimization of the present invention, the temperature classification standard of the motor is as follows: T1 represents the normal range: T1 < 75℃; T2 indicates overheating: 75℃ ≤ T2 < 90℃; T3 indicates severe overheating: T3 ≥ 90℃.
[0010] As a further optimization of the present invention, the classification of vibration levels is based on the root mean square value of vibration velocity, and the standard is as follows: V1 indicates the normal range: Vibration_RMS < 2.8 mm / s; V2 indicates mild vibration: 2.8 mm / s ≤ Vibration_RMS < 4.5 mm / s; V3 indicates severe vibration: Vibration_RMS ≥ 4.5 mm / s; Vibration_RMS refers to the root mean square value of the vibration signal, which represents the effective value or average energy of the vibration amplitude over a period of time. It is a key parameter for measuring the overall intensity of vibration.
[0011] As a further optimization of the present invention, the calculation steps of Vibration_RMS in the data processing module are as follows: S2-1, Signal Acquisition: The vibration sensor acquires the original vibration acceleration signal sequence a(n) over a period of time T at a set sampling frequency, where n is the sampling point number and the sequence length is N; S2-2, Signal preprocessing: The original vibration acceleration signal sequence a(n) is filtered and denoised to obtain the preprocessed acceleration signal sequence a'(n); S2-3. Calculate the root mean square value: The root mean square value of the vibration velocity is calculated based on the preprocessed acceleration signal sequence a'(n).
[0012] The beneficial effects of this invention are as follows: During use, the high-precision patch thermocouple and vibration sensor can continuously collect the temperature and vibration of the motor housing, enabling real-time observation of abnormal motor operation. When a problem is detected, the motor can be repaired in a timely manner, effectively preventing the fault from escalating, greatly improving the convenience and safety of use, and making it more convenient for people to use. Attached Figure Description
[0013] Figure 1 This is a schematic diagram of the overall structure of the diagnostic device of the present invention; Figure 2 This is a schematic diagram of the unfolded structure of the diagnostic device of the present invention; Figure 3 This is a partial structural schematic diagram of the diagnostic device of the present invention.
[0014] In the diagram: 1. Motor; 2. Vibration sensor; 3. First arc-shaped plate; 4. Fixing plate; 5. First mounting plate; 6. Second arc-shaped plate; 7. Second mounting plate; 8. First mounting hole; 9. Second mounting hole; 10. Surface mount thermocouple. Detailed Implementation
[0015] The present application will now be described in further detail with reference to the accompanying drawings. It should be noted that the following specific embodiments are only used to further illustrate the present application and should not be construed as limiting the scope of protection of the present application. Those skilled in the art can make some non-essential improvements and adjustments to the present application based on the above application content.
[0016] like Figure 1 - Figure 3 As shown, an electric tricycle motor diagnostic device includes a motor 1, and also includes: The vibration detection module includes a vibration sensor 2 that is fixedly installed on the top housing of the motor 1; Temperature monitoring module, the temperature monitoring module is installed on the outside of the motor 1 housing by a fixing mechanism; The temperature monitoring module includes a first arc plate 3 and a second arc plate 6 that can surround the outer shell of the motor 1. Fixing plates 4 are installed on the inner sidewalls of the first arc plate 3 and the second arc plate 6. High-precision patch thermocouples 10 that fit tightly against the outer shell of the motor 1 are installed on the side of the two fixing plates 4 closest to the motor 1.
[0017] The first arc plate 3 and the second arc plate 6 are fixedly connected by at least one set of connecting components. The connecting components include a first mounting plate 5 and a second mounting plate 7 respectively fixed on the first arc plate 3 and the second arc plate 6. The first mounting plate 5 and the second mounting plate 7 are respectively provided with a plurality of corresponding first mounting holes 8 and second mounting holes 9. Bolts pass through the corresponding first mounting holes 8 and second mounting holes 9 and are locked by nuts. The first arc plate 3, the second arc plate 6 and the fixing plate 4 are all made of high thermal conductivity material.
[0018] A vibration sensor 2 is fixedly installed on the housing at the top of the motor 1 by bolts to detect the vibration of the motor during operation. The temperature monitoring module can detect the temperature of the motor in real time. Two thermocouples 5 can make good contact with the surface of the motor 3 housing to ensure the accuracy of temperature measurement. During installation, bolts are passed through the corresponding first mounting hole 8 and second mounting hole 9 and locked with nuts to firmly fix the first arc plate 3 and the second arc plate 6 to the motor 3 housing. A diagnostic method for an electric tricycle motor includes the following steps: S1. Data acquisition: Real-time temperature data of motor 3 is acquired using high-precision patch thermocouple 5, and real-time vibration data of motor 3 is acquired using vibration sensor 2. S2. Data Analysis: The collected temperature and vibration data are uploaded to the data processing module. The data processing module compares the real-time temperature value with the preset temperature threshold and classifies it into three levels: T1, T2, and T3. At the same time, the data processing module calculates the root mean square value of the vibration data and compares the root mean square value with the preset vibration threshold and classifies it into three levels: V1, V2, and V3. S3, Data Transmission and Display Module: The data transmission module transmits the analyzed temperature level, vibration level and their corresponding values to the human-machine interaction module for real-time display. S4. Status Warning and Alarm Module: The human-machine interaction module performs the following operations based on the received level information: When the temperature display shows T2 or the vibration display shows V2, an audible and visual warning will be triggered to alert the user and prompt timely maintenance. When the temperature display shows T3 or the vibration display shows V3, a strong alarm will be triggered, and it is recommended to stop the vehicle immediately.
[0019] The temperature classification standards for motors are as follows: T1 represents the normal range: T1 < 75℃; T2 indicates overheating: 75℃ ≤ T2 < 90℃; T3 indicates severe overheating: T3 ≥ 90℃.
[0020] The classification of vibration levels is based on the root mean square value of vibration velocity, and the standard is as follows: V1 indicates the normal range: Vibration_RMS < 2.8 mm / s; V2 indicates mild vibration: 2.8 mm / s ≤ Vibration_RMS < 4.5 mm / s; V3 indicates severe vibration: Vibration_RMS ≥ 4.5 mm / s; Vibration_RMS refers to the root mean square value of the vibration signal, which represents the effective value or average energy of the vibration amplitude over a period of time. It is a key parameter for measuring the overall intensity of vibration.
[0021] The calculation steps for Vibration_RMS in the data processing module are as follows: S2-1, Signal Acquisition: The vibration sensor (2) acquires the original vibration acceleration signal sequence a(n) within a time period T at a set sampling frequency, where n is the sampling point number and the sequence length is N; S2-2, Signal preprocessing: The original vibration acceleration signal sequence a(n) is filtered and denoised to obtain the preprocessed acceleration signal sequence a'(n); S2-3. Calculate the root mean square value: Based on the preprocessed acceleration signal sequence a'(n), calculate the root mean square value of the vibration velocity. After the vehicle starts, two high-precision patch thermocouples 5 continuously collect surface temperature data of the motor 3 housing, and vibration sensor 2 collects the three-dimensional vibration acceleration signal of the motor. The collected temperature and data are transmitted via cable to a data processing module installed on the vehicle body. The data processing module calculates the average temperature every 10 seconds and compares it with a preset threshold: if the temperature is below 75℃, it is marked as T1 level; if the temperature is between 75℃ and 90℃, it is marked as T2 level; if the temperature is above or equal to 90℃, it is marked as T3 level. Simultaneously, the data processing module performs bandpass filtering on the vibration acceleration signal every 10 seconds to obtain a preprocessed signal a'(n), then converts it into a velocity signal through integration, and calculates the root mean square value (Vibration_RMS) of the velocity signal within that time period. If Vibration_RMS is less than 2.8 mm / s, it is marked as V1 level; if it is between 2.8 mm / s and 4.5 mm / s, it is marked as V2 level; if it is greater than or equal to 4.5 mm / s, it is marked as V3 level. The vibration level, measured in mm / s and marked as V3, is analyzed. The temperature level, vibration level, and their specific values are transmitted via CAN bus to the human-machine interface module (an LCD display) in the driver's cab. The screen clearly displays the current temperature (e.g., "82℃ T2") and vibration level (e.g., "3.1 mm / s V2"). When the display shows T2 or V2, the human-machine interface module triggers a flashing yellow warning light and an intermittent buzzer sound to remind the driver that "the motor temperature is too high" or "abnormal vibration, please be careful." If the condition worsens to T3 or V3, the warning light turns solid red, the buzzer emits a rapid and continuous alarm sound, and the display shows a warning message such as "Severe overheating, please stop immediately!" or "Severe vibration, danger!", forcing the driver to stop and check, thereby preventing an accident.
[0022] The embodiments described above are merely examples of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention.
Claims
1. A diagnostic device for an electric tricycle motor, comprising a motor (1), characterized in that, Also includes: Vibration detection module, the vibration detection module includes a vibration sensor (2) fixedly installed on the top housing of the motor (1); A temperature monitoring module is installed outside the motor (1) housing via a fixing mechanism; The temperature monitoring module includes a first arc plate (3) and a second arc plate (6) that can surround the outer shell of the motor (1). Fixing plates (4) are installed on the inner sidewalls of the first arc plate (3) and the second arc plate (6). High-precision patch thermocouples (10) that fit tightly against the outer shell of the motor (1) are installed on the side of the two fixing plates (4) near the motor (1).
2. The method for diagnosing the motor of an electric tricycle according to claim 1, characterized in that: The first arc plate (3) and the second arc plate (6) are fixedly connected by at least one set of connecting components. The connecting components include a first mounting plate (5) and a second mounting plate (7) fixed on the first arc plate (3) and the second arc plate (6) respectively. The first mounting plate (5) and the second mounting plate (7) are respectively provided with a plurality of corresponding first mounting holes (8) and second mounting holes (9). The bolt passes through the corresponding first mounting holes (8) and second mounting holes (9) and is locked by a nut.
3. The method for diagnosing the motor of an electric tricycle according to claim 1, characterized in that: The first arc plate (3), the second arc plate (6) and the fixing plate (4) are all made of high thermal conductivity material.
4. A method for diagnosing the motor of an electric tricycle according to any one of claims 1-3, characterized in that: Includes the following steps: S1. Data acquisition: The high-precision patch thermocouple (5) is used to acquire the real-time temperature data of the motor (3), and the vibration sensor (2) is used to acquire the real-time vibration data of the motor (3). S2. Data Analysis: The collected temperature and vibration data are uploaded to the data processing module. The data processing module compares the real-time temperature value with the preset temperature threshold and classifies it into three levels: T1, T2, and T3. At the same time, the data processing module calculates the root mean square value of the vibration data and compares the root mean square value with the preset vibration threshold and classifies it into three levels: V1, V2, and V3. S3, Data Transmission and Display Module: The data transmission module transmits the analyzed temperature level, vibration level and their corresponding values to the human-machine interaction module for real-time display. S4. Status Warning and Alarm Module: The human-machine interaction module performs the following operations based on the received level information: When the temperature display shows T2 or the vibration display shows V2, an audible and visual warning will be triggered to alert the user and prompt timely maintenance. When the temperature display shows T3 or the vibration display shows V3, a strong alarm will be triggered, and it is recommended to stop the vehicle immediately.
5. The method for diagnosing the motor of an electric tricycle according to claim 1, characterized in that: The temperature classification standard for the motor is as follows: T1 represents the normal range: T1 < 75℃; T2 indicates overheating: 75℃ ≤ T2 < 90℃; T3 indicates severe overheating: T3 ≥ 90℃.
6. The method for diagnosing the motor of an electric tricycle according to claim 1, characterized in that: The vibration level classification is based on the root mean square value of the vibration velocity, and the standard is as follows: V1 indicates the normal range: Vibration_RMS < 2.8 mm / s; V2 indicates mild vibration: 2.8 mm / s ≤ Vibration_RMS < 4.5 mm / s; V3 indicates severe vibration: Vibration_RMS ≥ 4.5 mm / s; Vibration_RMS refers to the root mean square value of the vibration signal, which represents the effective value or average energy of the vibration amplitude over a period of time. It is a key parameter for measuring the overall intensity of vibration.
7. The method for diagnosing the motor of an electric tricycle according to claim 1, characterized in that: The calculation steps for Vibration_RMS in the data processing module are as follows: S2-1, Signal Acquisition: The vibration sensor (2) acquires the original vibration acceleration signal sequence a(n) within a time period T at a set sampling frequency, where n is the sampling point number and the sequence length is N; S2-2, Signal preprocessing: The original vibration acceleration signal sequence a(n) is filtered and denoised to obtain the preprocessed acceleration signal sequence a'(n); S2-3. Calculate the root mean square value: The root mean square value of the vibration velocity is calculated based on the preprocessed acceleration signal sequence a'(n).