System and method for preventing spontaneous combustion and spontaneous explosion in wireless charging of electric bicycle

Abstract

The invention discloses an electric bicycle wireless charging self-ignition and self-explosion prevention system which comprises 1) a transmitting end which comprises a transmitting coil and an identification module, is installed on the ground and is used for transmitting electric energy to a receiving end arranged on an electric bicycle; the receiving end comprises a receiving coil, a battery and a receiving end identifier; the battery management module is arranged in the receiving end and used for monitoring real-time charging data of the battery in real time and uploading the real-time charging data to a background management system; the background management system comprises a battery information module and an intelligent charging model; and 5) a user front end which is in data connection with the background management system and is used for identifying the receiving end and checking the charging state, the historical charging record and the battery health degree evaluation information of the battery. The wireless charging self-ignition and self-explosion prevention system and method for the electric bicycle have good effects in the aspects of improving the charging safety, optimizing the charging efficiency, enhancing the user experience and the like.

Description

Technical Field

[0001] The invention relates to the field of wireless charging of electric bicycles, and in particular to a system and method for preventing spontaneous combustion and explosion of wireless charging of electric bicycles. Background Art

[0002] Wireless charging technology for electric bicycles can effectively solve the tediousness of plugging and unplugging wires in wired charging methods, and improve the convenience of charging. However, during the wireless charging process of electric bicycles, the safety of batteries has become increasingly prominent. Electric bicycles are often charged in or near personnel areas. Due to factors such as battery aging, unreasonable charging parameters, and harsh charging environment, the battery may overheat, spontaneously combust, or even explode during the charging process, which seriously threatens the personal and property safety of users.

[0003] At present, most of the bicycle wireless charging systems on the market still use fixed charging parameters for charging, and cannot be dynamically adjusted according to the real-time status and aging degree of the battery. This charging method not only has low charging efficiency, but also has great safety risks.

[0004] In addition, although some technologies have attempted to adjust charging parameters by monitoring battery status, these technologies are often limited to simple threshold judgments or fixed algorithms, lack sufficient intelligence and adaptability, and cannot accurately reflect the actual status and aging of the battery. Therefore, they are not effective in practical applications.

[0005] In order to solve the above problems, there is an urgent need for an electric bicycle wireless charging system and method that can prevent battery spontaneous combustion and explosion. Summary of the invention

[0006] The present invention introduces an intelligent charging model to dynamically adjust charging parameters according to real-time charging data and aging factors of the battery, thereby improving the charging efficiency of the electric bicycle, reducing safety hazards, and ensuring safe use of the user.

[0007] The first object of the present invention is to provide an electric bicycle wireless charging anti-spontaneous combustion and explosion system, comprising:

[0008] The transmitting end includes a transmitting coil and an identification module, which is installed on the ground and is used to transmit electric energy to a receiving end arranged on the electric bicycle, and the identification module is used to read the identification of the receiving end and identify the receiving end;

[0009] A receiving end, comprising a receiving coil, a battery and a receiving end identifier, wherein the receiving coil is used to receive the electric energy transmitted by the transmitting end and convert it into direct current electric energy suitable for charging the battery, and the receiving end identifier is used to identify the receiving end;

[0010] A battery management module is provided in the receiving end, and is used to monitor the real-time charging data of the battery in real time, and upload the real-time charging data to a background management system;

[0011] A backend management system, comprising a battery information module and an intelligent charging model, wherein the battery information module stores basic information of the battery, and the intelligent charging model determines and adjusts charging parameters in real time according to the basic information of the battery and the real-time charging data;

[0012] The user front end is connected to the data of the background management system to identify the receiving end and view the battery charging status, historical charging records and battery health assessment information through the background management system.

[0013] Preferably, the battery management module is arranged in the receiving end, and includes a voltage monitoring module, a current monitoring module and a temperature monitoring module; the real-time charging data includes real-time charging voltage, real-time charging current and real-time temperature data.

[0014] Preferably, the basic battery information includes battery model, battery rated capacity, battery rated voltage, production date, manufacturer and battery serial number.

[0015] Preferably, the receiving end identifier is a wireless communication tag or a QR code; the wireless communication tag is a radio frequency identification tag or a near field communication tag.

[0016] The second object of the present invention is to provide a method for preventing spontaneous combustion and explosion of an electric bicycle by wireless charging. In the aforementioned system for preventing spontaneous combustion and explosion of an electric bicycle by wireless charging, the following steps are adopted:

[0017] S1. Identify the receiving end through the user front end and upload the basic information of the battery in the receiving end to the backend management system;

[0018] S2. Before charging starts, the identification module of the transmitter identifies the receiver and sends a charging request to the background management system. The background management system starts the intelligent charging model and sets the initial charging parameters according to the output of the intelligent charging model.

[0019] S3. During the charging process, the battery management module monitors the real-time charging data of the battery in real time and transmits this data to the background management system;

[0020] S4, the background management system applies the intelligent charging model and adjusts the charging parameters in real time according to the real-time charging data received from the battery management module;

[0021] S5. Once the battery management module finds an abnormality, it immediately activates the receiving end protection mechanism, stops charging, and sends abnormal data to the user's front-end and back-end management systems;

[0022] S6. The background management system performs fault analysis based on the real-time charging data or abnormal data uploaded by the battery management module. When an abnormality is detected, the transmitter protection mechanism is activated, charging is stopped, and maintenance suggestions are generated.

[0023] S7. If there is no abnormality, the battery is fully charged, the transmitter stops supplying power, and charging is completed.

[0024] Preferably, the intelligent charging model is a neural network-based model, and the neural network model dynamically adjusts the charging parameters according to the battery aging factor and real-time charging data.

[0025] Preferably, the neural network type is a convolutional neural network, including an input layer, a convolution layer, a pooling layer and a fully connected layer.

[0026] Preferably, in step S2, the identification module of the transmitting end identifies the receiving end through the receiving end identifier of the receiving end.

[0027] Preferably, in step S4, the intelligent charging model dynamically adjusts the charging parameters according to the battery aging factor and real-time charging data, and the aging factor includes years of use, number of charges, depth of discharge, and temperature history.

[0028] Preferably, the intelligent charging model is established by the following steps:

[0029] 1) Determine the optimization target of the smart charging model;

[0030] 2) Collect charging data of electric bicycle batteries and perform preprocessing;

[0031] 3) Select the type and structure of neural network used in the smart charging model;

[0032] 4) Design the structure of the neural network of the intelligent charging model;

[0033] 5) Train and verify the established intelligent charging model;

[0034] 6) Optimize and deploy the established smart charging model.

[0035] The electric bicycle wireless charging anti-spontaneous combustion and explosion system and method of the present invention have the following beneficial effects:

[0036] 1) By real-time monitoring of the real-time charging data (such as voltage, current, temperature) of the electric bicycle battery and the degree of battery aging (such as service life, number of charging times, etc.), the present invention can dynamically adjust the charging parameters, effectively avoiding safety hazards such as battery overheating, spontaneous combustion and even explosion caused by unreasonable charging parameters, thereby greatly improving the safety of the charging process.

[0037] 2) The application of intelligent charging model makes the charging process more intelligent and personalized. For batteries in good health, the system can use a higher current and higher voltage charging mode to shorten the charging time and improve the charging efficiency. For batteries that are seriously aged, a low current and low voltage charging mode is used to reduce thermal effects and extend the battery life.

[0038] 3) A dual protection mechanism is introduced. The battery management module and the background management system can respectively start the protection mechanism at the receiving end and the transmitting end, making the wireless charging of electric bicycles safer and more reliable.

[0039] 4) Through the interaction between the user front-end and the back-end management system, the present invention allows users to conveniently view information such as the battery charging status, historical charging records, and battery health assessment, thereby enhancing the user experience. At the same time, in the event of an abnormality, the system can promptly send an alarm to the user, reminding the user to take appropriate measures, further ensuring the user's safety.

[0040] The electric bicycle wireless charging anti-spontaneous combustion and explosion system and method of the present invention have good effects in improving charging safety, optimizing charging efficiency, enhancing user experience, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a module block diagram of an electric bicycle wireless charging anti-spontaneous combustion and explosion system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to further understand the present invention, the embodiments of the present invention are described below in conjunction with examples, but it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, rather than limiting the claims of the present invention.

[0043] Embodiment 1

[0044] The embodiment of the present invention provides a wireless charging anti-spontaneous combustion and explosion system for electric bicycles, such as Figure 1 As shown, it includes a receiving end, a transmitting end, a battery management module, a background management system, a user front end and other parts.

[0045] The transmitter, including a transmitting coil and an identification module, is installed on the ground and has an electromagnetic induction transmission function, and is used to transmit electric energy to a receiving end arranged on the electric bicycle. The identification module of the transmitter is used to obtain the receiving end identification and identify the receiving end.

[0046] The receiving end includes a receiving coil, a battery, a receiving end identifier and other parts. The receiving coil is installed at the bottom of the electric bicycle or a designated location, and has an electromagnetic induction receiving function. It is used to receive the electric energy transmitted by the wireless transmitter and convert it into DC power suitable for battery charging. The receiving end identifier can be a wireless communication tag, which is used to identify the receiving end. Specifically, it can be an RFID (Radio Frequency Identification) tag or an NFC (Near Field Communication) tag. When the wireless communication tag of the receiving end is read, the receiving end is identified. The receiving end identifier can also be a QR code, which is also used to identify the receiving end.

[0047] The battery management module can be set in the receiving end, including a voltage monitoring module, a current monitoring module, a temperature monitoring module, etc., for real-time monitoring of the real-time charging data of the battery. The real-time charging data includes real-time charging voltage, real-time charging current, real-time temperature and other data. The battery management module exchanges data with the background management system through wireless communication methods, such as Wi-Fi or Bluetooth.

[0048] The backend management system includes battery information module and intelligent charging model. The battery information module stores basic battery information. The basic battery information includes:

[0049] 1) Battery model: Indicates the specifications and type of the battery, such as lithium battery, lead-acid battery, etc.

[0050] 2) Battery rated capacity: Indicates the battery's ability to store electrical energy. The larger the capacity, the more power the battery can provide, and the longer the driving range. It is usually measured in ampere-hours (Ah).

[0051] 3) Battery rated voltage: Indicates the voltage value of the battery when it is working normally, usually in volts (V).

[0052] 4) Production Date: The manufacturing date of the battery helps users understand the shelf life and service life of the battery.

[0053] 5) Manufacturer: The company or brand that produces the battery, usually related to the quality and after-sales service of the battery.

[0054] 6) Battery Serial Number: A number used to uniquely identify a battery, which helps track and identify the battery if it fails or requires repair.

[0055] At the same time, the background management system determines the initial charging parameters through the intelligent charging model. Charging parameters include charging current, charging voltage and other parameters. In addition, the background management system applies the intelligent charging model based on the real-time charging data uploaded by the battery management module, adjusts the charging parameters in real time, evaluates the aging of the battery, and predicts potential safety hazards.

[0056] The user front end can be an APP or applet set on a mobile phone, which is connected to the backend management system data wirelessly. The user front end includes a receiving end reading module and a charging information module. The receiving end reading module can obtain the information of the receiving end, including the basic information of the battery, by scanning the QR code on the receiving end or reading the wireless communication tag, and then upload it to the backend management system.

[0057] The charging information module can conveniently view the battery charging status, historical charging records, battery health assessment and other information through the background management system, enhancing the user experience. At the same time, in the event of an abnormality, the background management system can use the charging information module to send an alert to the user in a timely manner.

[0058] The embodiment of the present invention provides an electric bicycle wireless charging anti-spontaneous combustion and explosion system, which can monitor the battery status in real time and dynamically adjust the charging parameters, thereby effectively preventing the battery from spontaneous combustion and explosion and improving the charging efficiency and safety.

[0059] Embodiment 2

[0060] The embodiment of the present invention provides a method for preventing spontaneous combustion and explosion of an electric bicycle through wireless charging, which comprises the following steps:

[0061] S1. Identify the receiving end through the user front end and upload the basic information of the battery in the receiving end to the background management system.

[0062] The receiving end can be identified by scanning a QR code or a wireless communication tag on the receiving end. The wireless communication tag can be an RFID tag or an NFC tag. The receiving end can be identified by a receiving end reading module at the user's front end when the receiving end is installed on the electric bicycle, or before the receiving end is ready to be charged for the first time through the anti-spontaneous combustion and explosion system.

[0063] S2. Before charging starts, the identification module of the transmitter identifies the receiver and sends a charging request to the background management system. The background management system starts the intelligent charging model and sets the initial charging parameters according to the output of the model. The charging parameters include charging current, charging voltage and other parameters.

[0064] The identification module of the transmitting end can identify the receiving end through the wireless communication tag of the receiving end.

[0065] S3. During the charging process, the battery management module monitors the real-time charging data of the battery in real time and transmits the data to the background management system. The real-time charging data includes real-time charging voltage, real-time charging current, real-time temperature and other data.

[0066] S4. The background management system applies the intelligent charging model and adjusts the charging parameters in real time according to the real-time charging data received from the battery management module.

[0067] S5. Once the battery management module detects an abnormality, such as abnormal current fluctuations, sharp temperature rise, etc., it immediately activates the receiving end protection mechanism, stops charging, and sends an alarm to the user's front-end and back-end management systems.

[0068] S6. The backend management system performs fault analysis based on the real-time charging data or abnormal data uploaded by the battery management module. When an abnormality is detected, the transmitter protection mechanism is activated, charging is stopped, and maintenance suggestions are generated. At the same time, the backend management system records the data of each charging process for subsequent battery health assessment and intelligent charging model optimization.

[0069] The background management system can analyze the abnormal data uploaded by the battery management module and start the transmitter protection mechanism when it is abnormal. The background management system can also analyze the real-time charging data uploaded by the battery management module and start the transmitter protection mechanism when it is abnormal. The anti-spontaneous combustion and explosion system introduces a dual protection mechanism. The battery management module and the background management system can start the protection mechanism at the receiving end and the transmitting end respectively, making the wireless charging of electric bicycles safer and more reliable.

[0070] S7. If there is no abnormality, the battery is fully charged, the transmitter stops supplying power, and charging is completed.

[0071] The intelligent charging model in the method for preventing spontaneous combustion and explosion of wireless charging of an electric bicycle according to an embodiment of the present invention dynamically adjusts the charging parameters according to the aging degree factor of the battery and the real-time charging data. The aging degree factor includes factors such as the service life, the number of charging times, the depth of discharge, and the temperature history. For severely aged batteries, a low current and low voltage charging mode is adopted to reduce the thermal effect and the stress inside the battery. For batteries in good health, a higher current and higher voltage charging mode can be adopted to improve the charging efficiency.

[0072] The establishment of the intelligent charging model can be based on a neural network model, which is established in the following steps:

[0073] 1) Determine the optimization objectives of the smart charging model.

[0074] Optimization goals may include preventing battery overheating or spontaneous combustion, optimizing charging efficiency, reducing charging time, etc.

[0075] 2) Collect charging data of electric bicycle batteries and perform preprocessing.

[0076] Collect charging history data of electric bicycle batteries, including charging time, charging current, charging voltage, battery temperature, battery capacity, battery aging, etc. Clean the data to remove invalid or abnormal data. Standardize or normalize the data to ensure that data with different characteristics are on the same scale.

[0077] 3) Select the type and structure of neural network used in the smart charging model.

[0078] Choose the appropriate neural network type based on the complexity of the problem and the characteristics of the data. The data during the charging process is a time series data, and convolutional neural network is a more suitable choice for processing this type of data.

[0079] 4) Design the structure of the neural network of the intelligent charging model. Determine the number of layers of the neural network, the number of neurons in each layer, the activation function, etc.

[0080] For the input layer, the input features include the real-time status of the battery (such as voltage, current, temperature) and the degree of battery aging.

[0081] The convolution layer can be set to include the first convolution layer, the second convolution layer, and the pooling layer. The number of convolution kernels of the first convolution layer can be set to 32, the convolution kernel size can be set to 3x3, the step size is 1, and the activation function is ReLU (Rectified Linear Unit). The number of convolution kernels of the second convolution layer can be set to 64, the convolution kernel size can be set to 3x3, the step size is 1, and the activation function is ReLU. The pooling layer can set the pooling type to Max Pooling, the pooling window size to 2x2, and the step size to 2.

[0082] The first layer of the fully connected layer can be set to 128 neurons and the activation function can be ReLU. The second layer of the fully connected layer can be used as the output layer, and the number of neurons can be determined according to the output requirements, including the charging parameters, for example, it can be set to 32.

[0083] A suitable loss function is selected according to the optimization objective of the smart charging model. For example, the mean square error (MSE) can be used as the loss function.

[0084] 5) Train and verify the established intelligent charging model.

[0085] The data set is divided into training set, validation set and test set. The training set is used to train the model, the validation set is used to adjust the model parameters, and the test set is used to evaluate the model performance. The training set data is used to train the neural network. During the training process, indicators such as the change in the loss function and the accuracy of the model can be monitored. The validation set data is used to verify the trained model and evaluate the performance of the model.

[0086] 6) Optimize and deploy the established smart charging model.

[0087] The model is further optimized based on the test results, such as fine-tuning the network structure, etc. The trained model is deployed to the background management system of the wireless charging of electric bicycles, which receives the real-time status data of the receiving end and outputs the appropriate charging parameters.

[0088] The smart charging model can help establish an efficient and accurate method to prevent spontaneous combustion and explosion through reasonable data preparation, model design, training and optimization, deployment and monitoring.

[0089] The embodiment of the present invention provides a method for preventing spontaneous combustion and explosion of an electric bicycle during wireless charging. By introducing an intelligent charging model, real-time charging data and aging degree of a battery are monitored in real time, and charging parameters are dynamically adjusted, thereby effectively preventing spontaneous combustion and explosion of the battery and improving charging efficiency and safety.

[0090] The above embodiments are only used to help understand the method and core idea of ​​the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

Claims

1. An electric bicycle wireless charging anti-spontaneous combustion and explosion system, characterized in that: include: The transmitting end includes a transmitting coil and an identification module, which is installed on the ground and is used to transmit electric energy to a receiving end arranged on the electric bicycle, and the identification module is used to read the identification of the receiving end and identify the receiving end; A receiving end, comprising a receiving coil, a battery and a receiving end identifier, wherein the receiving coil is used to receive the electric energy transmitted by the transmitting end and convert it into direct current electric energy suitable for charging the battery, and the receiving end identifier is used to identify the receiving end; A battery management module is provided in the receiving end, and is used to monitor the real-time charging data of the battery in real time, and upload the real-time charging data to a background management system; A backend management system, comprising a battery information module and an intelligent charging model, wherein the battery information module stores basic information of the battery, and the intelligent charging model determines and adjusts charging parameters in real time according to the basic information of the battery and the real-time charging data; The user front end is connected to the data of the background management system to identify the receiving end and view the battery charging status, historical charging records and battery health assessment information through the background management system.

2. The electric bicycle wireless charging anti-spontaneous combustion and explosion system according to claim 1 is characterized in that: The battery management module is arranged in the receiving end, and includes a voltage monitoring module, a current monitoring module and a temperature monitoring module; the real-time charging data includes real-time charging voltage, real-time charging current and real-time temperature data.

3. The electric bicycle wireless charging anti-spontaneous combustion and explosion system according to claim 1 is characterized in that: The basic battery information includes battery model, battery rated capacity, battery rated voltage, production date, manufacturer and battery serial number.

4. The electric bicycle wireless charging anti-spontaneous combustion and explosion system according to any one of claims 1 to 3, characterized in that: The receiving end identifier is a wireless communication tag or a QR code; the wireless communication tag is a radio frequency identification tag or a near field communication tag.

5. A method for preventing spontaneous combustion and explosion of wireless charging of electric bicycles, characterized in that: In the electric bicycle wireless charging anti-spontaneous combustion and explosion system according to any one of claims 1 to 4, the following steps are adopted: S1. Identify the receiving end through the user front end and upload the basic information of the battery in the receiving end to the backend management system; S2. Before charging starts, the identification module of the transmitter identifies the receiver and sends a charging request to the background management system. The background management system starts the intelligent charging model and sets the initial charging parameters according to the output of the intelligent charging model. S3. During the charging process, the battery management module monitors the real-time charging data of the battery in real time and transmits this data to the background management system; S4, the background management system applies the intelligent charging model and adjusts the charging parameters in real time according to the real-time charging data received from the battery management module; S5. Once the battery management module finds an abnormality, it immediately activates the receiving end protection mechanism, stops charging, and sends abnormal data to the user's front-end and back-end management systems; S6. The background management system performs fault analysis based on the real-time charging data or abnormal data uploaded by the battery management module. When an abnormality is detected, the transmitter protection mechanism is activated, charging is stopped, and maintenance suggestions are generated. S7. If there is no abnormality, the battery is fully charged, the transmitter stops supplying power, and charging is completed.

6. The method for preventing spontaneous combustion and explosion of wireless charging of electric bicycles according to claim 5, characterized in that: The intelligent charging model is a neural network-based model, and the neural network model dynamically adjusts the charging parameters according to the battery aging factor and real-time charging data.

7. The method for preventing spontaneous combustion and explosion of wireless charging of electric bicycles according to claim 6, characterized in that: The neural network type is a convolutional neural network, which includes an input layer, a convolution layer, a pooling layer and a fully connected layer.

8. The method for preventing spontaneous combustion and explosion of wireless charging of electric bicycles according to claim 5, characterized in that: In step S2, the identification module of the transmitting end identifies the receiving end through the receiving end identifier of the receiving end.

9. The method for preventing spontaneous combustion and explosion of wireless charging of electric bicycles according to claim 5, characterized in that: In step S4, the intelligent charging model dynamically adjusts the charging parameters according to the battery aging factors and real-time charging data, wherein the aging factors include service life, number of charges, depth of discharge, and temperature history.

10. The method for preventing spontaneous combustion and explosion of an electric bicycle by wireless charging according to any one of claims 5 to 9, characterized in that: The smart charging model is established using the following steps: 1) Determine the optimization target of the smart charging model; 2) Collect charging data of electric bicycle batteries and perform preprocessing; 3) Select the type and structure of neural network used in the smart charging model; 4) Design the structure of the neural network of the intelligent charging model; 5) Train and verify the established intelligent charging model; 6) Optimize and deploy the established smart charging model.

Images