Charging pile anti-collision system and method

Abstract

The invention discloses an anti-collision system and method for a charging pile, and aims to solve the problem that the early warning capability of a traditional anti-collision scheme is insufficient. The system comprises an infrared distance measurement module, an embedded control module, a local alarm module and a wireless communication module. The method comprises the following steps that the infrared distance measuring sensor collects and sends real-time distance data; the embedded control module performs fitting processing and threshold judgment after receiving the data, and outputs alarm level information; the local alarm module responds according to the alarm level information; and the wireless communication module transmits the alarm information to a remote terminal. Through the system and the method, data noise can be effectively filtered, the data accuracy can be improved, multi-dimensional alarm and remote monitoring can be realized, the problem of insufficient early warning capability of a traditional anti-collision scheme is solved, and the safety and the user experience of a charging station are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of safety protection for electric vehicle charging facilities, and in particular to a charging pile anti-collision system and method. Background Art

[0002] With the rapid adoption of new energy vehicles and the continued expansion of charging infrastructure, safety and security issues at charging stations are becoming increasingly prominent. During charging, collisions between vehicles and charging stations due to driver misuse or environmental factors are common. This not only damages the equipment but can also pose safety risks. Currently, charging station collision avoidance primarily relies on physical protective structures or basic sensor technology, but these solutions have significant limitations. While physical protective structures can mitigate collision impact, they cannot proactively provide early warning. Ultrasonic sensors, while capable of detecting distance, are susceptible to interference from ambient noise, leading to frequent false alarms or missed alerts.

[0003] Among the existing technologies for safety monitoring of charging piles, the patent with publication number CN106375946A proposes a charging pile monitoring system based on a wireless sensor network. This technology uses an embedded processor and a wireless sensor network to achieve real-time monitoring of the internal parameters of the charging pile, and uses the improved LEACH-C routing protocol to optimize network energy consumption. Although this solution has advantages in equipment status monitoring and network energy consumption management, its original design intention was to solve the problem of remote monitoring of the internal parameters of the charging pile, resulting in its technical focus being concentrated on the internal status monitoring of the charging process, and no external collision protection is involved. Specifically, the system is capable of real-time monitoring, but lacks dedicated sensors for vehicle distance detection, and is unable to achieve real-time anti-collision warning functions, making it difficult to meet the actual needs of charging stations for vehicle collision protection.

[0004] In summary, there is an urgent need for a new collision avoidance system that can combine high-precision ranging technology, real-time data processing and intelligent warning functions to solve the problems of insufficient ranging accuracy, large response delay and single protection function in existing technologies, so as to fill the technical gap in the existing charging pile collision avoidance field. Summary of the Invention

[0005] The purpose of the present invention is to provide a charging pile anti-collision system and method to overcome the problem of insufficient early warning capability of traditional anti-collision solutions.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a charging pile anti-collision system, comprising:

[0008] Infrared ranging module, used to collect the distance data between the vehicle and the charging pile in real time and send the distance data to other modules;

[0009] Embedded control module, used to receive distance data and perform data fitting and threshold judgment, and output alarm level information;

[0010] The local alarm module receives the alarm level information from the embedded control module and responds;

[0011] The wireless communication module receives the alarm level information from the embedded control module and transmits it to the remote terminal.

[0012] The infrared ranging module collects distance data based on the principle of triangulation.

[0013] The embedded control module adopts the NI myRIO embedded platform and is equipped with a data fitting program programmed by LabVIEW software to realize data fitting and threshold judgment.

[0014] The local alarm module includes:

[0015] Sound alarm module, used to generate corresponding alarm sound prompts according to the alarm level information;

[0016] The indicator light module is used to generate corresponding alarm visual prompts according to the alarm level information.

[0017] The wireless communication module is equipped with Bluetooth and Wi-Fi dual-mode communication, and uses the MQTT protocol to synchronize data to the cloud server.

[0018] In a second aspect, the present invention provides a charging pile anti-collision method, comprising the following steps:

[0019] The infrared ranging sensor collects the real-time distance data between the vehicle and the charging pile and sends the distance data;

[0020] The embedded control module receives the distance data and performs data fitting, performs threshold judgment on the fitted distance data, and outputs alarm level information;

[0021] The local alarm module receives the alarm level information and responds;

[0022] The wireless communication module receives the alarm level information and transmits it to the remote terminal.

[0023] The embedded control module receives the distance data and performs data fitting, performs threshold judgment on the fitted distance data, and outputs alarm level information, including:

[0024] The embedded control module receives the distance data, and the data fitting program in the embedded control module performs data fitting processing on the distance data to obtain fitted distance data;

[0025] The fitted distance data is compared with the set threshold to obtain the alarm level information and output it.

[0026] The data were fitted using a linear fitting model.

[0027] The data fitting process includes:

[0028] The received distance data is converted into x and y components, and the data point of the received data is (x i ,y i ), the data point satisfies t i ≈a+bx i , i=1,2,…,n。

[0029] Set the threshold to:

[0030] S = 60cm, identified as the third level alarm;

[0031] 20cm≤S<60cm, identified as the second level alarm;

[0032] S<20cm, identified as the first level alarm;

[0033] Among them, S is the distance information after fitting.

[0034] Compared with the prior art, the present invention has the following beneficial technical effects:

[0035] The charging pile anti-collision system provided by the present invention collects the distance data between the vehicle and the charging pile in real time through the infrared ranging module, and sends this data to the embedded control module. The embedded control module performs fitting processing and threshold judgment on the data, which can effectively filter out the noise and interference in the data, improve the accuracy and reliability of the data, and thus more accurately identify potential collision risks. The local alarm module responds with sound and light alarms according to the alarm level information, reminding users to pay attention to safety in an intuitive and multi-dimensional manner, avoiding insufficient warnings caused by a single prompt method. The wireless communication module transmits the alarm information to the remote terminal to realize remote monitoring and management, breaking through the limitation of traditional solutions that are limited to local reminders, and greatly improving the practicality and safety of the system. In summary, the system effectively overcomes the problem of insufficient early warning capabilities of traditional anti-collision solutions through precise data collection, data processing, multi-dimensional alarm prompts and remote monitoring functions.

[0036] The core of the charging pile collision avoidance method provided by the present invention lies in processing and judging the collected distance data. First, the infrared ranging sensor collects the distance data between the vehicle and the charging pile in real time, ensuring the timeliness and accuracy of the information from the source. Next, the embedded control module performs fitting processing on the data. This step can effectively reduce the data fluctuations caused by environmental factors, making the data smoother and more reliable. After that, the alarm level is determined by threshold judgment. This process realizes a quantitative assessment of the degree of risk and avoids the problem of inaccurate warning in traditional solutions. The local alarm module takes corresponding response measures according to the alarm level, such as sound alarm and flashing indicator light, to remind the user from both auditory and visual dimensions, enhancing the communication effect of the warning information. Finally, the wireless communication module transmits the alarm information to the remote terminal, so that the management personnel can grasp the on-site situation in a timely manner and take necessary measures. Overall, this method constructs a comprehensive intelligent collision avoidance warning system through real-time monitoring, intelligent analysis, accurate warning and remote monitoring, effectively solving the problem of insufficient warning capability of traditional collision avoidance solutions. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 Schematic diagram of a charging pile anti-collision system in an embodiment of the present invention.

[0038] Figure 2 The figure is a flow chart of a charging pile anti-collision method according to an embodiment of the present invention.

[0039] Figure 3 The figure is a schematic diagram of a data fitting process in a charging pile collision avoidance method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0040] With the rapid adoption of new energy vehicles and the continued expansion of charging infrastructure, safety and security issues at charging stations are becoming increasingly prominent. During charging, collisions between vehicles and charging stations due to driver misuse or environmental factors are common. This not only damages the equipment but can also pose safety risks. Currently, charging station collision avoidance primarily relies on physical protective structures or basic sensor technology, but these solutions have significant limitations. While physical protective structures can mitigate collision impact, they cannot proactively provide early warning. Ultrasonic sensors, while capable of detecting distance, are susceptible to interference from ambient noise, leading to frequent false alarms or missed alerts.

[0041] Based on the above background, the present invention provides a charging pile anti-collision system and method. By introducing advanced infrared ranging technology, an embedded control platform and wireless communication technology, this solution realizes high-precision real-time monitoring of the distance between the vehicle and the charging pile, intelligent early warning and multi-terminal synchronous alarm, thereby improving the early warning capability and effectively overcoming the shortcomings of traditional solutions.

[0042] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0043] Reference Figure 1 As shown in FIG, a specific embodiment of the charging pile collision avoidance system provided by the present invention includes:

[0044] Infrared ranging module, used to collect the distance data between the vehicle and the charging pile in real time and send the distance data to other modules;

[0045] Embedded control module, used to receive distance data and perform data fitting and threshold judgment, and output alarm level information;

[0046] A local alarm module receives the alarm level information of the embedded control module and responds;

[0047] The wireless communication module receives the alarm level information of the embedded control module and transmits it to the remote terminal.

[0048] Specifically, the system's main control processor is the NImyRIO embedded platform, or embedded control module, contained within the charging station. Its primary function is to receive and process data from the infrared ranging sensor. The NI myRIO embedded platform is equipped with a data fitting program programmed in LabVIEW software, which implements data fitting and threshold determination. The embedded control module is connected to the infrared ranging sensor, which, based on the principle of triangulation, accurately collects real-time data on the distance between the electric vehicle and the charging station. This data is then transmitted to the NI myRIO processor via an I / O interface.

[0049] After analyzing and processing the data, the NI myRIO processor in the embedded control module transmits it to a local mobile monitoring terminal for display via Bluetooth wireless communication technology. Simultaneously, the data is uploaded to the cloud, allowing remote mobile monitoring terminals to access the relevant information.

[0050] During data processing, the data fitting program in the NI myRIO processor first performs fitting and noise reduction on the collected data. It then compares the noise-reduced data with a pre-set threshold and, based on the comparison results, determines the alarm level, outputting the alarm level information. This alarm level information is then received by the local alarm module and the wireless communication module. In this embodiment, the local alarm module includes an audible alarm module and an indicator light alarm module. The audible alarm module is specifically a 5V active electromagnetic buzzer module, capable of responding to different alarm levels by adjusting its operating frequency to produce buzzer prompts with varying tones, thereby achieving an alarm effect. The indicator light alarm module is specifically comprised of several indicator lights mounted on the charging station body. The number of indicator lights preferably corresponds to the number of alarm levels. In this embodiment, the alarm levels are three, so the number of indicator lights is preferably a multiple of three. It should be noted that other numbers of indicator lights can also achieve the same effect. Depending on the alarm level, the indicator light module responds by lighting a different number of lights to provide a visual warning effect. Furthermore, the local alarm module may also include an LCD module mounted on the charging station body, which displays the distance between the vehicle and the charging station in real time.

[0051] The wireless communication module transmits alarm level information to a remote mobile phone monitoring terminal via a network microdata terminal. In this specific embodiment, the wireless communication module utilizes Bluetooth and Wi-Fi dual-mode communication and uses the MQTT protocol to synchronize data to a cloud server. Upon receiving the alarm level information, the module transmits a signal to the user terminal via Bluetooth or Wi-Fi. The system then triggers a prompt on the remote user terminal to alert the user. Preferably, the user terminal displays the following information: alarm level information, such as level 1, level 2, and level 3 alarms; and vehicle distance information, which updates the distance between the vehicle and the charging station in real time and displays it on the user terminal.

[0052] To achieve more accurate measurement and early warning capabilities, this system employs advanced data processing algorithms. Specifically, the system utilizes the triangulation principle of infrared ranging sensors to collect real-time data on the distance between the vehicle and the charging station. This principle precisely measures the time between infrared emission and reflection to calculate the actual distance between the vehicle and the charging station.

[0053] In terms of data transmission, this system not only enables local display but also uploads analyzed and processed measurement data to the user's remote terminal via Bluetooth communication technology, facilitating remote monitoring, extending beyond the alarm mode of the charging pile itself. Furthermore, the embedded control module can also connect to the manufacturer's PC monitoring terminal, sending data to the manufacturer's PC monitoring terminal, allowing charging pile manufacturers to remotely monitor data and achieve real-time monitoring and management of charging pile status.

[0054] The system's NI myRIO processor plays a crucial role in measuring data processing and decision-making. After setting thresholds in the system's LabVIEW program, the processor displays the data collected by the sensors and compares the data with the thresholds to determine the alarm level. The system also features audible and visual alarms to alert users when necessary, effectively enhancing the system's early warning capabilities and user experience.

[0055] On the other hand, refer to Figure 1 The figure shows a flow chart of a specific embodiment of the charging pile collision avoidance method provided by the present invention, including:

[0056] The infrared ranging sensor collects the real-time distance data between the vehicle and the charging pile and sends the distance data;

[0057] The embedded control module receives the distance data and performs data fitting, performs threshold judgment on the fitted distance data, and outputs alarm level information;

[0058] The local alarm module receives the alarm level information and responds;

[0059] The wireless communication module receives the alarm level information and transmits it to the remote terminal.

[0060] Specifically, the infrared ranging sensor collects real-time distance data between the vehicle and the charging station and transmits this data. Upon receiving this distance data, the embedded control module performs data fitting and noise reduction. The embedded control module then performs a threshold determination on the fitted distance data. This fitted distance data is compared with the set threshold to determine the alarm level and output it. A linear fitting model is used for data fitting.

[0061] The threshold value is set as follows:

[0062] When the distance S=60cm, it is identified as the third level alarm;

[0063] When the distance is 20cm≤S<60cm, it is identified as the second level alarm;

[0064] When the distance S is less than or equal to 20 cm, it is identified as a first-level alarm.

[0065] In this specific embodiment, when the system detects that the distance between the vehicle and the charging station reaches 60cm, that is, entering the warning threshold, the local alarm module activates the sound and light alarm. Specifically, when it is identified as a third-level alarm (S = 60cm), the sound alarm module frequency is 50Hz, and the indicator module lights up one light; when it is identified as a second-level alarm (20cm≤S<60cm), the sound alarm module frequency is 500Hz, and the indicator module lights up two lights; when it is identified as a first-level alarm (S<20cm), the sound alarm module frequency is 5kHz, and the indicator module lights up three lights.

[0066] In the actual measurement process, due to environmental factors (such as temperature changes, electromagnetic interference, etc.) or the limitations of the measurement equipment, the collected distance data may contain certain noise and errors. Figure 3 As shown, in order to reduce the impact of random errors and thus more accurately reflect the actual distance change trend between the vehicle and the charging pile, a data fitting process is added to this solution. Through data fitting, these raw data can be smoothed. Data fitting can simplify these complex data points into a relatively simple mathematical model (such as a linear fitting model), which is convenient for subsequent analysis and processing.

[0067] After receiving the input of the independent and dependent variable data, the data fitting program of this system can convert the tabular data into x and y components. Different fitting methods and corresponding fitting models can then be selected according to actual needs, such as least squares, least absolute residual, Bisquarre, etc. In this specific embodiment, a default fitting method is specified. When other models cannot produce good results for the data, the default fitting method will be selected for data fitting. The default fitting method is preferably the least squares method.

[0068] After determining the fitting method, the data fitting program will proceed to select a fitting model. You can choose a linear, polynomial, exponential, or power function model. If you choose a polynomial fitting model, you will need to further select the order. Finally, the data fitting program will output the corresponding fitting equation and display an XY graph from the parameters. The accuracy and mean square error will also be displayed for a more intuitive view of the data fitting results. Similarly, the selection of the fitting model also provides a default fitting model, which is preferably a linear fitting model in this specific embodiment.

[0069] The theoretical basis of data fitting is to assume that the given data point (x i ,y i ), where i = 1, 2, ..., n is distributed roughly in a straight line. Although the fitted line cannot be required to pass through every data point, it should be as close to these points as possible.

[0070] To achieve this goal, the criterion for constructing a fitted line is typically to minimize the sum of squared residuals. Residuals are defined as the difference between the actual data points and the corresponding points on the fitted line. The system calculates the sum of squared residuals for all data points and uses mathematical methods such as least squares to determine the optimal parameters for the fitted line, thereby obtaining the optimal fitted line equation.

[0071] Although we cannot require the fitting straight line y = a + bx, we can still obtain:

[0072] t i ≈a+bx i , i=1,2,…,n

[0073] Here, the number of data points is usually much larger than the number of coefficients to be determined. Therefore, the construction of a fitted line is essentially an algebraic problem of solving an overdetermined system of equations. Suppose:

[0074]

[0075] The difference between the two is called the residual. Obviously, the size of the residual obtained by the system is an important indicator of the quality of data fitting. Specifically, the criterion of minimizing the sum of squares of the residuals can be used to construct the fitting curve, that is:

[0076] ∑|e i |=min

[0077] Specifically in this system, during the data fitting process, the system receives a set of data points containing independent and dependent variables. These data points represent the distance measurement between the vehicle and the charging station, as well as the corresponding timestamp or other related variables. The system uses the independent variable of these data points as the x-component and the dependent variable as the y-component. Users can select an appropriate fitting method from the system's provided fitting method library, such as linear fitting and polynomial fitting, based on the actual application scenario and data characteristics. Based on the selected method and model, the system will use mathematical algorithms such as the least squares method to calculate the optimal fitting parameters, generate the corresponding fitting equation, and display the fitting results graphically to help users better understand data trends and characteristics.

[0078] In practical applications, the choice of data fitting is crucial to the accuracy and reliability of measurement results. For example, when a vehicle approaches a charging station at a slow speed, the distance data may change relatively smoothly, and a linear fitting model can well describe this trend. However, when the vehicle moves at a faster speed or in an irregular manner, a higher-order fitting model may be required to capture the complex variation pattern. Therefore, this system provides a variety of fitting methods and models to suit different measurement scenarios and needs.

[0079] Furthermore, data fitting results are not only used for real-time monitoring and early warning, but also provide an important basis for subsequent data analysis and system optimization. By fitting and analyzing large amounts of historical data, the system can identify common vehicle approach patterns and potential collision risk scenarios, thereby further optimizing threshold settings and alarm strategies, improving overall system performance and user experience.

[0080] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions are merely preferred examples of the present invention and are not intended to limit the present invention. Various changes and improvements may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and improvements fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A charging pile anti-collision system, characterized in that: include: Infrared ranging module, used to collect the distance data between the vehicle and the charging pile in real time and send the distance data to other modules; Embedded control module, used to receive distance data and perform data fitting and threshold judgment, and output alarm level information; A local alarm module receives the alarm level information from the embedded control module and responds; The wireless communication module receives the alarm level information of the embedded control module and transmits it to the remote terminal.

2. A charging pile anti-collision system according to claim 1, characterized in that: The infrared ranging module collects distance data based on the triangulation principle.

3. The charging pile anti-collision system according to claim 1, characterized in that: The embedded control module adopts the NI myRIO embedded platform and is equipped with a data fitting program programmed with LabVIEW software to achieve data fitting and threshold judgment.

4. The charging pile anti-collision system according to claim 1, characterized in that: The local alarm module includes: Sound alarm module, used to generate corresponding alarm sound prompts according to the alarm level information; The indicator light module is used to generate corresponding alarm visual prompts according to the alarm level information.

5. The charging pile anti-collision system according to claim 1, characterized in that: The wireless communication module is equipped with Bluetooth and Wi-Fi dual-mode communication, and uses the MQTT protocol to synchronize data to the cloud server.

6. A charging pile anti-collision method, characterized in that: The following steps are involved: The infrared ranging sensor collects the real-time distance data between the vehicle and the charging pile and sends the distance data; The embedded control module receives the distance data and performs data fitting, performs threshold judgment on the fitted distance data, and outputs alarm level information; The local alarm module receives the alarm level information and responds; The wireless communication module receives the alarm level information and transmits it to the remote terminal.

7. A charging pile anti-collision method according to claim 6, characterized in that: The embedded control module receives the distance data and performs data fitting, performs threshold judgment on the fitted distance data, and outputs alarm level information, including: The embedded control module receives the distance data, and the data fitting program in the embedded control module performs data fitting processing on the distance data to obtain fitted distance data; The fitted distance data is compared with the set threshold to obtain the alarm level information and output it.

8. A charging pile anti-collision method according to claim 7, characterized in that: The data fitting was performed using a linear fitting model.

9. A charging pile anti-collision method according to claim 8, characterized in that: The data fitting process includes: The received distance data is converted into x and y components, and the data point of the received data is (x i ,y i ), the data point satisfies y i ≈a+bx i , i=1,2,…,n。 10. A charging pile anti-collision method according to claim 7, characterized in that: The set threshold is: S = 60cm, identified as the third level alarm; 20cm≤S<60cm, identified as the second level alarm; S<20cm, identified as the first level alarm; Among them, S is the distance information after fitting.

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