A UWB-based wireless charging alignment system and control method thereof

Abstract

A wireless charging alignment system based on UWB, the wireless charging alignment system includes a parking space, a parking space baffle arranged on the parking space, and a charging panel arranged in the middle of the parking space; a lifting mechanism is arranged below the charging panel to control the charging panel to rise to achieve high-efficiency transmission with the receiving coil; a transmitting coil that can run along the X-axis and Y-axis tracks is arranged on the lower side of the lifting mechanism, and the X-axis and Y-axis tracks are both composed of screws driven by motor control; a touch sensor is arranged on the upper part of the charging panel to detect whether the charging panel reaches the bottom of the vehicle; four UWB ranging base stations are installed around the parking space to measure the distance from the positioning tag at the location of the receiving coil at the bottom of the vehicle; the four UWB ranging base stations, the lifting mechanism, the touch sensor and the motor that controls the movement of the transmitting coil inside the charging panel are respectively connected to the system control processor. The present invention can realize high-precision positioning of the positioning tag at the location of the receiving coil.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless charging, and in particular to a UWB-based wireless charging alignment system and a control method thereof. Background Art

[0002] The current market share of electric vehicles is gradually increasing, but they are also facing some problems, such as battery life, which limits the performance of electric vehicles. The main strategies at present are charging piles and battery replacement. As a new charging method, wireless charging technology has the advantages of being fast, safe, and intelligent. It has been widely used in digital electronic products, and some manufacturers have begun to work on wireless charging of electric vehicles, which has great potential in the future.

[0003] For wireless charging, transmission power and system efficiency are important indicators for evaluating wireless charging. However, during the wireless charging process, if the transmitting coil and the receiving coil cannot be reliably aligned, the relevant transmission indicators will be greatly affected. Therefore, the degree of coupling between the transmitting coil and the receiving coil is one of the important factors affecting the efficiency of wireless charging. Since it is difficult to achieve precise alignment of the transmitting coil and the receiving coil when charging electric vehicles, it is difficult to obtain the maximum coupling coefficient, making wireless charging unable to be carried out quickly and effectively. For the current application, on the one hand, the driver adjusts the vehicle through the in-car image to align the position of the receiving coil with the transmitting coil, and on the other hand, the coil structure is redesigned to improve the anti-drift ability of the coil.

[0004] In comparison, the alignment of the vehicle side by the driver requires multiple adjustments, which increases the burden on the driver. On the other hand, it is necessary to deploy imaging equipment on the vehicle side, which increases the cost and is not conducive to large-scale promotion and application. The coil structure is redesigned and is only used when the offset is small, and the transmission efficiency and transmission power are not high. When a large offset occurs, charging is no longer possible.

[0005] Therefore, for vehicle wireless charging, the offset and distance of the coupling mechanism are the biggest problems affecting power and transmission efficiency. How to better align the two is an issue that needs to be solved urgently. Summary of the invention

[0006] In response to the above-mentioned technical problems, the present technical solution provides a UWB-based wireless charging alignment system and a control method thereof, which improves the parking space during the wireless charging process, has low cost and high positioning accuracy, and can effectively solve the coil positioning problem.

[0007] The present invention is achieved through the following technical solutions:

[0008] A control method for a wireless charging alignment system based on UWB, the wireless charging alignment system comprising a parking space and a parking space baffle arranged on the parking space; a charging panel is arranged in the middle of the parking space, and a lifting mechanism is arranged below the charging panel to control the charging panel to rise to achieve high-efficiency transmission with a receiving coil; a transmitting coil that can run along an X-axis and a Y-axis track is arranged inside the charging panel, and the X-axis and Y-axis tracks are both composed of screws driven by a motor control; a touch sensor is arranged on the upper part of the charging panel to detect whether the charging panel reaches the bottom of the vehicle; four UWB ranging base stations are installed around the parking space to measure the distance to the positioning tag where the receiving coil is located at the bottom of the vehicle; the four UWB ranging base stations, the lifting mechanism, the touch sensor and the motor that controls the movement of the transmitting coil inside the charging panel are respectively connected to the system control processor; when the user parks the vehicle in the parking space as required, the four UWB ranging base stations located around the parking space are started, and the distance between each base station and the positioning tag of the receiving coil at the bottom of the vehicle is preliminarily measured by UWB technology;

[0009] The SSA optimized ELM classification algorithm first expands the features of the original data, uses the least squares method to solve the approximate coordinates according to the distance from the label to the four base stations, and then inversely calculates the approximate coordinates and the estimated distances of the four base stations to obtain d1′, d2′, d3′, d4′, and then calculates the difference between the estimated distances d1′, d2′, d3′, d4′ and the initial measured distances d1, d2, d3, d4 of the base stations to obtain Δd1, Δd2, Δd3, Δd4; finally, the distance difference and As one feature data, the feature data finally calculated has 5 dimensions, and the order is d1, d2, d3, d4, Considering that the initial weights and thresholds of ELM are randomly generated, SSA is used to optimize the initial weights and thresholds, and the fitness function is designed as the sum of the error rate of the training set and the error rate of the test set; the specific steps are as follows:

[0010] Step 1: Start the system and use UWB ranging to locate the distance between the tag and four base stations;

[0011] Step 2: Use the least square method to obtain the approximate coordinate value based on the ranging value, and then use the coordinate value to inversely solve the distance between the tag and each base station. Then, based on the difference between the two, calculate the total error value. Based on the five feature data of the ranging value and the total error value, use the SSA optimized ELM classification algorithm to divide the data into normal values ​​and abnormal values;

[0012] Step 3: According to the results obtained in step 2, two models of normal data and abnormal data are established; first, according to the particle swarm algorithm, by establishing different objective functions, a total of four groups of approximate solutions are solved, and then combined with the approximate solution obtained by the least squares method in step 2, five groups of feature data are formed as the data predicted in step 4; for normal data, the coordinates estimated by the least squares method are used as the initial position of the particle swarm algorithm, and there are five groups of approximate solutions, which are the least squares approximate solution plus the four groups of approximate solutions of the particle swarm; for abnormal data, the initial position is randomly generated by the position range of the charging panel, and there are four groups of approximate solutions, which are the four groups of approximate solutions of the particle swarm;

[0013] Step 4: Get the approximate solutions of different models according to step 3, use them as the input of ridge regression prediction, and use the real coordinates of the positioning labels as the output, and train them to get the final coordinates;

[0014] Step 5: Move the transmitting coil to the designated position, raise the charging module, and stick it to the bottom of the car to start charging.

[0015] Furthermore, the X-axis and Y-axis tracks are arranged on the lower side of the lifting mechanism, and the charging panel, as well as the transmitting coil and the lifting mechanism inside the charging panel can all be moved along the tracks in the X-axis motion mechanism and the Y-axis motion mechanism; the charging panel, as well as the transmitting coil and the lifting mechanism inside the charging panel are all installed on the X-axis motion mechanism, so that the relevant mechanisms of the charging panel move along the X-axis direction on the X-axis track; the X-axis motion mechanism is installed on the Y-axis motion mechanism, so that the relevant mechanisms of the charging panel follow the X-axis motion mechanism to move along the Y-axis track direction of the Y-axis motion mechanism; in this way, under the drive of the motors in the X-axis motion mechanism and the Y-axis motion mechanism, the transmitting coil on the inner panel of the charging panel can reach any position within the parking area.

[0016] Furthermore, the UWB technology is to obtain d i (i=1,2,3,4), when the distance value has no error, it must satisfy (x i -x) 2 +(y i -y) 2 +(z i -z) 2 =d i 2 , where (x i ,y i , z i ) is the coordinate information of each base station, and (x, y, z) is the coordinate information of the positioning tag.

[0017] Beneficial Effects

[0018] The UWB-based wireless charging alignment system and control method proposed in the present invention have the following beneficial effects compared with the prior art:

[0019] (1) The present invention uses the coordination of a liftable charging panel installed in the middle of the parking space, a mobile device arranged in cooperation with the charging panel, a baffle arranged in the parking space, and ranging base stations arranged around the parking space, and uses UWB technology, SSA optimized ELM classification algorithm, particle swarm algorithm, and least squares method to achieve high-precision coordinate prediction of the positioning tag, and verifies it through a test set, so as to achieve high-precision positioning of the vehicle receiving coil; and uses the mobile device located at the bottom of the vehicle, that is, arranged on the parking space, and in combination with the total stroke S obtained through calculation, calculates the optimal running time of the motor, adjusts the position of the transmitting coil, and achieves precise displacement of the transmitting coil, so that the alignment operation of the coupling mechanism in the transmitting coil and the receiving coil at the bottom of the vehicle can maintain good accuracy even under the interference of external signals. It can effectively achieve high-efficiency operation of wireless charging, solve the problem of alignment coil offset, and provide convenience for the driver.

[0020] (2) The present invention optimizes the ELM classification algorithm through SSA, which can determine whether the ranging value of the current ranging base station is interfered with, and optimizes the fitness function weight of the particle swarm algorithm using the coefficient of variation method, thereby improving the particle's optimization ability.

[0021] (3) The present invention uses an algorithm to accurately locate the position of the receiving coil at the bottom of the vehicle, solving the problem of inaccurate coil positioning. And by optimizing the movement of the bottom transmitting coil movement mechanism, it is ensured that the travel error of the transmitting coil is reduced as much as possible during the movement process. It can reduce the driver's operation and bring convenience to the driver. On the other hand, by deploying base stations and positioning adjustment equipment in the parking space, the cost of deploying vehicle positioning devices can be reduced.

[0022] (4) The present invention optimizes the control time of the motion mechanism and adopts different operation strategies for the motor according to the different strokes, thereby solving the problem of the travel error caused by the start and stop time of the motor causing a certain error influence on the movement of the moving mechanism; it realizes the precise movement of the transmitting coil and ensures the precise alignment operation between the coupling mechanisms, which can effectively realize the high-efficiency operation of wireless charging. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic diagram of the stationary state of the vehicle in Embodiment 1 of the present invention.

[0024] Figure 2 It is a schematic diagram of a parking space in embodiment 1 of the present invention.

[0025] Figure 3It is a schematic diagram of the structure of the charging panel in Example 1 of the present invention.

[0026] Figure 4 It is a schematic diagram of the change of the speed of the motion mechanism over time in Example 1 of the present invention.

[0027] Figure 5 This is a flowchart of coordinate prediction in Example 2 of the present invention.

[0028] Figure 6 3 is a comparison chart of the errors and accuracies of various algorithms in Example 2 of the present invention. DETAILED DESCRIPTION

[0029] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. The described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. Under the premise of not departing from the design concept of the present invention, various modifications and improvements made by ordinary persons in the art to the technical solutions of the present invention should all fall within the protection scope of the present invention.

[0030] Embodiment 1:

[0031] like Figure 1-3 As shown, a UWB-based wireless charging alignment system includes a parking space and a parking space baffle arranged on the parking space; a charging panel is arranged in the middle of the parking space, and a lifting mechanism is arranged below the charging panel to control the charging panel to rise to achieve high-efficiency transmission with the receiving coil; a transmitting coil that can run along the X-axis track and the Y-axis track is arranged inside the charging panel, and the X-axis track and the Y-axis track are both composed of screws driven by a motor; a touch sensor is arranged on the upper part of the charging panel to detect whether the charging panel reaches the bottom of the vehicle; four UWB ranging base stations are installed around the parking space to measure the distance to the positioning tag where the receiving coil is located at the bottom of the vehicle; the four UWB ranging base stations, the lifting mechanism, the touch sensor and the motor that controls the movement of the transmitting coil inside the charging panel are respectively connected to the system control processor.

[0032] The X-axis track and the Y-axis track are arranged at the lower side of the lifting mechanism, and the charging panel, as well as the transmitting coil and the lifting mechanism inside the charging panel can be moved along the tracks in the X-axis motion mechanism and the Y-axis motion mechanism; the charging panel, as well as the transmitting coil and the lifting mechanism inside the charging panel are all installed on the X-axis motion mechanism, so that the relevant mechanisms of the charging panel move along the X-axis direction on the X-axis track; the X-axis motion mechanism is installed on the Y-axis motion mechanism, so that the relevant mechanisms of the charging panel follow the X-axis motion mechanism to move along the Y-axis track direction of the Y-axis motion mechanism; in this way, driven by the motors in the X-axis motion mechanism and the Y-axis motion mechanism, the transmitting coil on the inner panel of the charging panel can reach any position within the parking area.

[0033] like Figure 4 As shown in the figure, when the motor starts and stops, it will first accelerate, then maintain a constant speed, then decelerate, and finally the speed drops to 0. There are certain requirements for the stroke. In order to avoid errors, the motor running time needs to be controlled to a certain extent. For a given motor and designed mechanism, the acceleration a1, a2, v of its motion mechanism * , t * , t ** is known; a1 is the acceleration of the motion mechanism when it accelerates to a uniform speed, a2 is the acceleration of the motion mechanism when the motor stops running and reduces its speed from a uniform speed to 0; v * is the speed at uniform speed; t * is the time required for the moving mechanism to reach a uniform speed, t ** is the time required for the velocity to decrease from a constant speed to 0.

[0034] Embodiment 2:

[0035] like Figure 5 As shown, a control method of a wireless charging alignment system based on UWB controls a wireless charging alignment system based on UWB described in Example 1. When the user parks the vehicle in the parking space as required, the four UWB ranging base stations located around the parking space are started, and the distance between each base station and the positioning tag of the receiving coil at the bottom of the vehicle is preliminarily measured through UWB technology; first, the original data is divided into two models through the SSA optimized ELM classification algorithm, and then five groups of coordinates are predicted through the particle swarm algorithm and the least squares method, and these groups of coordinates are used as feature data for ridge regression prediction to obtain the final coordinates; finally, the mobile transmitting coil reaches the specified position, the charging module rises, and is close to the bottom of the car to perform charging operations. The specific operation steps are as follows:

[0036] Step 1: Start the system and use UWB ranging to locate the distance between the tag and four base stations.

[0037] UWB technology is initially obtained through UWB ranging i(i=1,2,3,4), when the distance value has no error, it must satisfy (x i -x) 2 +(y i -y) 2 +(z i -z) 2 =d i 2 , where (x i ,y i , z i ) is the coordinate information of each base station, and (x, y, z) is the coordinate information of the positioning tag.

[0038] Step 2: Use the least squares method to obtain the approximate coordinate value based on the ranging value, and then use the coordinate value to inversely solve the distance between the tag and each base station. Then, based on the difference between the two, calculate the total error value. Based on the five feature data of the ranging value and the total error value, use the SSA optimized ELM classification algorithm to divide the data into normal values ​​and abnormal values.

[0039] The SSA optimized ELM classification algorithm first expands the features of the original data, uses the least squares method to solve the approximate coordinates according to the distance from the label to the four base stations, and then inversely calculates the approximate coordinates and the estimated distances of the four base stations to obtain d1′, d2′, d3′, d4′, and then calculates the difference between the estimated distances d1′, d2′, d3′, d4′ and the initial measured distances d1, d2, d3, d4 of the base stations to obtain Δd1, Δd2, Δd3, Δd4; finally, the distance difference and As one feature data, the feature data finally calculated has 5 dimensions, and the order is d1, d2, d3, d4, Considering that the initial weights and thresholds of ELM are randomly generated, SSA is used to optimize the initial weights and thresholds, and the fitness function is designed as the sum of the error rate of the training set and the error rate of the test set.

[0040] Step 3: Based on the results obtained in step 2, the classification algorithm of ELM is optimized by SSA, and the input data can be divided into normal data and abnormal data, and two models of normal data and abnormal data can be established.

[0041] For normal data, the coordinates estimated by the least squares method are used as the initial position of the particle swarm algorithm. There are five groups of approximate solutions, which are the least squares approximate solution plus the four groups of approximate solutions of the particle swarm algorithm. For abnormal data, the initial position is randomly generated by the position range of the charging panel. There are four groups of approximate solutions, which are the four groups of approximate solutions of the particle swarm.

[0042] According to the particle swarm algorithm, by establishing different objective functions, a total of four groups of approximate solutions are solved, and then combined with the approximate solution obtained by the least squares method in step 2, five groups of feature data are formed as the data predicted in step 4.

[0043] Five sets of coordinates are predicted by particle swarm algorithm and least square method. For normal data, the coordinates estimated by least square method are used as the initial position of particle swarm algorithm. For abnormal data, the initial position is randomly generated by the position range of charging panel. The approximate coordinates of the tag are solved by particle swarm optimization algorithm, and its objective function is the sum of the distances from the tag to the three spheres. The sum of the distances from the tag P to the three spheres is used as one objective function. There are a total of 4 base stations that establish 4 spheres, so 4 objective functions can be obtained by combining them. The following is the objective function of the particle swarm optimization algorithm when solving the target point, where i, j, and k are any three combinations of 1, 2, 3, and 4, respectively.

[0044]

[0045] When there is no error, the distance from the tag to each base station should be equal to the distance measurement value of each base station, that is, (xx i ) 2 +(yy i ) 2 +(zz i ) 2 -d i 2 =ε, i = 1, 2, 3, 4, ε is the deviation between the square of the coordinate calculation from the tag to each base station and the square of the distance measurement value of the i-th base station; under ideal conditions, ε is 0, but due to the existence of deviation, ε is not 0; so the total deviation is:

[0046]

[0047] Among them, ω i The weight of the deviation between the square of the coordinate calculation of the tag to the i-th base station and the square of the distance measurement value of the i-th base station is used as the fitness function of the particle swarm algorithm.

[0048] For the weight coefficient ω i The value of is determined by the coefficient of variation method, denoted as:

[0049] (xx i ) 2 +(yy i ) 2 +(zz i ) 2 -d i 2 =R i ,

[0050] (i=1,2,3,4), since this data has one index, so R=[R1 R2 R3 R4] T ;

[0051] Since the deviation requires the data value to be as small as possible, a negative indicator is used to perform a positive operation on R, that is,

[0052]

[0053] Since this data only has one indicator, no standardization is required. is the mean value of the indicator, and the standard deviation So the coefficient of variation Weight coefficient

[0054] Step 4: Get the approximate solutions of different models according to step 3, use them as the input of ridge regression prediction, and use the real coordinates of the positioning labels as the output, and train them to get the final coordinates.

[0055] Step 5: Move the transmitting coil to the designated position, raise the charging module, and stick it to the bottom of the car to start charging.

[0056] The above approximate solution is used as the feature data of the ridge regression algorithm, and the actual positioning label coordinates are used as the output. The following is verified with specific data.

[0057] In the application scenario of 5000mm*5000mm*5000mm, a batch of data was obtained through actual measurement, and the data set was divided into 10 parts, 9 of which were used as training sets and 1 as test sets. By comparing the algorithm in this paper, the least squares method and the ridge regression, the average error was used to compare the accuracy of each dimension and different algorithms. The following table and Figure 6 The error and accuracy comparison charts of each algorithm are shown respectively.

[0058]

[0059] Through the above table and Figure 6 The data can be analyzed to obtain: For abnormal data, the least square method performs very poorly and is not suitable for obtaining approximate solutions for abnormal data; for the Z axis, since the system does not need to know this value in actual applications, the accuracy of the system for the plane direction can be greatly improved. Figure 6It can be seen that in terms of precision error, the proposed algorithm has greatly improved compared with the least squares method and ridge regression, especially for abnormal data, the effect is more significant. On the XY plane, the proposed algorithm improves 24.75% and 30.22% respectively for normal data and 94.55% and 15.67% respectively for abnormal data compared with the least squares method and ridge regression.

[0060] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any changes, substitutions and improvements within the technical scope disclosed by the present invention are within the protection scope of the present invention.

Claims

1. A control method for a wireless charging alignment system based on UWB, wherein the wireless charging alignment system comprises a parking space and a parking space baffle disposed on the parking space; characterized in that: A charging panel is arranged in the middle of the parking space, and a lifting mechanism is arranged below the charging panel for controlling the charging panel to rise to achieve high-efficiency transmission with the receiving coil; a transmitting coil that can run along the X-axis and Y-axis tracks is arranged inside the charging panel, and the X-axis and Y-axis tracks are both composed of screws driven by motor control; a touch sensor is arranged on the upper part of the charging panel for detecting whether the charging panel reaches the bottom of the vehicle; four UWB ranging base stations are installed around the parking space for measuring the distance to the positioning tag where the receiving coil is located at the bottom of the vehicle; the four UWB ranging base stations, the lifting mechanism, the touch sensor and the motor for controlling the movement of the transmitting coil inside the charging panel are respectively connected to the system control processor; when the user parks the vehicle in the parking space as required, the four UWB ranging base stations located around the parking space are started, and the distance between each base station and the positioning tag of the receiving coil at the bottom of the vehicle is preliminarily measured by UWB technology; The SSA optimized ELM classification algorithm first expands the features of the original data, uses the least squares method to solve the approximate coordinates according to the distance from the label to the four base stations, and then inversely calculates the approximate coordinates and the estimated distances of the four base stations to obtain d1′, d2′, d3′, d4′, and then calculates the difference between the estimated distances d1′, d2′, d3′, d4′ and the initial measured distances d1, d2, d3, d4 of the base stations to obtain Δd1, Δd2, Δd3, Δd4; finally, the distance difference and As one feature data, the feature data finally calculated has 5 dimensions, and the order is d1, d2, d3, d4, Considering that the initial weights and thresholds of ELM are randomly generated, SSA is used to optimize the initial weights and thresholds, and the fitness function is designed as the sum of the error rate of the training set and the error rate of the test set; the specific steps are as follows: Step 1: Start the system and use UWB ranging to locate the distance between the tag and four base stations; Step 2: Use the least square method to obtain the approximate coordinate value based on the ranging value, and then use the coordinate value to inversely solve the distance between the tag and each base station. Then, based on the difference between the two, calculate the total error value. Based on the five feature data of the ranging value and the total error value, use the SSA optimized ELM classification algorithm to divide the data into normal values ​​and abnormal values; Step 3: According to the results obtained in step 2, two models of normal data and abnormal data are established; first, according to the particle swarm algorithm, by establishing different objective functions, a total of four groups of approximate solutions are solved, and then combined with the approximate solution obtained by the least squares method in step 2, five groups of feature data are formed as the data predicted in step 4; for normal data, the coordinates estimated by the least squares method are used as the initial position of the particle swarm algorithm, and there are five groups of approximate solutions, which are the least squares approximate solution plus the four groups of approximate solutions of the particle swarm; for abnormal data, the initial position is randomly generated by the position range of the charging panel, and there are four groups of approximate solutions, which are the four groups of approximate solutions of the particle swarm; Step 4: Get the approximate solutions of different models according to step 3, use them as the input of ridge regression prediction, and use the real coordinates of the positioning labels as the output, and train them to get the final coordinates; Step 5: Move the transmitting coil to the designated position, raise the charging module, and stick it to the bottom of the car to start charging.

2. The control method of a UWB-based wireless charging alignment system according to claim 1, characterized in that: The X-axis and Y-axis tracks are arranged at the lower side of the lifting mechanism, and the charging panel, as well as the transmitting coil and the lifting mechanism inside the charging panel can all be moved along the tracks in the X-axis motion mechanism and the Y-axis motion mechanism; the charging panel, as well as the transmitting coil and the lifting mechanism inside the charging panel are all installed on the X-axis motion mechanism, so that the relevant mechanisms of the charging panel move along the X-axis direction on the X-axis track; the X-axis motion mechanism is installed on the Y-axis motion mechanism, so that the relevant mechanisms of the charging panel follow the X-axis motion mechanism to move along the Y-axis track direction of the Y-axis motion mechanism; in this way, driven by the motors in the X-axis motion mechanism and the Y-axis motion mechanism, the transmitting coil on the inner panel of the charging panel can reach any position within the parking area.

3. The control method of a UWB-based wireless charging alignment system according to claim 1, characterized in that: The UWB technology described above is based on the initial acquisition of d by UWB ranging. i (i=1,2,3,4), when the distance value has no error, it must satisfy (x i -x) 2 +(y i -y) 2 +(z i -z) 2 =d i 2 , where (x i ,y i , z i ) is the coordinate information of each base station, and (x, y, z) is the coordinate information of the positioning tag.

Images