Efficient and stable wireless charging method and system for pressure-bearing lithium batteries

Abstract

This invention provides a highly efficient and stable wireless charging method suitable for pressurized lithium batteries, addressing the shortcomings of existing maximum efficiency tracking control methods, such as high time complexity, slow solution speed, and low maximum tracking speed, as well as the inaccuracy of charging process due to pressure affecting lithium battery parameters. This invention employs an improved perturbation-observation-golden section algorithm to achieve fast maximum efficiency tracking and stable control of pressurized lithium batteries. First, by comparing the current solution with the previous and next solutions, if the current solution is simultaneously better than both the previous and next solutions, the interval containing the optimal solution can be determined. Second, maximum efficiency tracking is performed using the golden section search algorithm. The time complexity of the golden section search algorithm is typically O(log n), where n is the dimension of the solution space. Therefore, using the perturbation-observation-golden section method can improve the efficiency and stability of wireless charging for pressurized lithium batteries to a certain extent.

Description

Technical Field

[0001] This invention belongs to the field of underwater wireless charging technology, specifically relating to a highly efficient and stable wireless charging method and system suitable for pressurized lithium batteries. Background Technology

[0002] Pressure-bearing lithium batteries, capable of directly withstanding pressure and whose internal characteristics change with external pressure, protect their structural components and are therefore of great significance in deep-sea applications of autonomous underwater vehicles (AUVs). While already in use, the lack of an in-situ, efficient energy replenishment method severely limits AUVs' operating time, speed, and depth, significantly restricting the scope and effectiveness of underwater operations. Therefore, underwater wireless power transmission technology, which eliminates physical contact, avoids sparks, and prevents interface exposure, is being applied to AUV energy replenishment. Wireless charging systems consist of a transmitter and a receiver, with maximizing charging efficiency being a key focus. Achieving maximum system efficiency requires maximum efficiency tracking control. Current solutions mostly involve transmitting receiver operating parameters (such as voltage and current) to the transmitter via a wireless communication network. The transmitter then uses derived formulas to calculate the optimal DC / DC voltage value, thus achieving maximum efficiency. This calculation method can achieve accurate maximum efficiency, but it requires wireless communication. However, wireless communication is prone to interference in the strong magnetic field environment of wireless charging, leading to problems such as packet loss and connection interruption.

[0003] Chinese patent CN111509865B discloses a maximum efficiency tracking control method and system for a wireless charging system, and Chinese patent application CN110571899A discloses a constant current output control and efficiency improvement method for a wireless power transfer system based on the variable step-size perturbation-observation method. Both of these schemes can achieve maximum efficiency tracking without requiring wireless communication. However, these maximum efficiency tracking control methods are all based on the perturbation-observation method, which is a greedy algorithm. It starts from a point in the solution space and moves towards neighboring points until it reaches a locally optimal solution where it cannot move further. The time complexity of a typical greedy algorithm is usually linear or near-linear, i.e., O(log n), where n is the dimension of the solution space. Its high time complexity results in a slow solution speed and a low maximum tracking speed. Summary of the Invention

[0004] This invention addresses the problems of current pressure-bearing lithium battery parameters being affected by pressure, and the high time complexity, slow solution speed, and low maximum tracking speed of current maximum efficiency tracking control methods. It provides an efficient and stable wireless charging method suitable for pressure-bearing lithium batteries.

[0005] To achieve the above objectives, the technical solution provided by this invention is:

[0006] A highly efficient and stable wireless charging method suitable for pressure-bearing lithium batteries, characterized by the following steps:

[0007] Step 1: Determine the stable output voltage range of the primary-side DC-DC converter

[0008] Step 1.1: A pressure-bearing lithium battery is a soft-pack battery that is directly exposed to seawater and withstands seawater pressure. As pressure increases, the internal characteristic parameters of the pressure-bearing lithium battery change; the resistance decreases monotonically, while the terminal voltage and actual usable capacity increase. Therefore, it is necessary to obtain the current SOC value (SOC0) of the pressure-bearing lithium battery and the equivalent load resistance R under different pressures. Li And the actual usable charge C of a pressure-bearing lithium battery with SOC=1 under different pressures. i ;

[0009] Step 1.2: Based on the equivalent load resistance R under different pressures Li The battery charging power P set by the wireless charging system out The voltage gain G set by the wireless charging system determines the stable output voltage range [V] suitable for the primary-side DC-DC converter of the pressurized lithium battery. inmin V inmax ];

[0010] Step 2: Determine the optimal efficiency operating point

[0011] Step 2.1: Existence determination stage of the optimal solution

[0012] Based on the stable output voltage range of the primary-side DC-DC converter determined in step 1, from the maximum output voltage V inmax Initially, decrease the value twice using its minimum resolution, and take V(1) = V inmax V(2)=V inmax -ΔV and V(3) = V(2) -ΔV are used as input voltages, and the corresponding input power P is calculated respectively. in (1) P in (2) and P in (3); where ΔV is the minimum resolution of the output voltage of the primary-side DC-DC converter;

[0013] If P in (1) <P in (2) <P in (3) Then the maximum output voltage V of the primary side DC-DC converter inmax Select the optimal output voltage value for system efficiency. Maximum efficiency tracking ends. Proceed to step 3.

[0014] Otherwise, proceed to step 2.2;

[0015] Step 2.2: Improved Disturbance Observation Phase

[0016] Within the stable output voltage range of the primary-side DC-DC converter, the output voltages are arranged in descending order (V). inmax -V inmin The step size ΔV' is decreased successively using V(k-1) / 10 (thus, the optimal solution interval can be determined in a maximum of 10 iterations). V(k-1) = V(k-2) - ΔV', V(k) = V(k-1) - ΔV', and V(k+1) = V(k) - ΔV' are used as the input voltages in sequence, and the corresponding input power P is calculated for each. in (k-1), P in (k) and P in (k+1); k takes values ​​from 2 to 9, and during the iteration process:

[0017] If P in (k+1)>P in (k) <P in If (k-1), then the optimal output voltage range for system efficiency is [V(k+1), V(k-1)], proceed to step 2.3;

[0018] If P in (k+1)>P in (k)≥P in If (k-1), then the optimal output voltage range for system efficiency is [V(k), V(k-1)], proceed to step 2.3;

[0019] If P always exists in (k+1) <P in (k) <P in (k-1), until V(k+1)≤V inmin (In practice, the minimum output voltage of the primary-side DC-DC converter is V) inmin However, during the judgment process, a further iteration may be performed to obtain the calculated value. Therefore, during the judgment process, V(k+1) can be less than V. inmin Then the minimum output voltage V of the primary-side DC-DC converter is... inmin Select the optimal output voltage value for system efficiency. Maximum efficiency tracking ends. Proceed to step 3.

[0020] In the method of this invention, P is not considered in order to avoid more judgments. in (k+1)=P in In the case of (k), the judgment logic and process can be simplified.

[0021] Step 2.3: Golden Ratio Search Phase

[0022] Using the golden section search algorithm, the optimal output voltage value is selected within the range of the optimal output voltage selected in step 2.2, and then proceed to step 3;

[0023] Step 3: Determine if the pressure-bearing lithium battery is fully charged.

[0024] Using the optimal output voltage selected in step 2 as the input voltage, the pressurized lithium battery is charged, and the SOC value of the pressurized lithium battery is acquired in real time during the charging process. t Until SOC t =1 indicates that the pressurized lithium battery is fully charged and charging has stopped; where,

[0025]

[0026] In the formula, t is the charging time, and I t Let C be the charging current at time t. N C represents the total charge of the battery under normal pressure, and ΔC represents the error in the actual usable charge of the battery due to pressure changes. i The appropriate value can be selected based on the pressure borne by the pressure-bearing lithium battery, and then ΔC = C i -C N The difference between the actual usable charge of the battery under different pressures and the total charge of the battery under normal pressure was calculated.

[0027] Meanwhile, this invention provides a highly efficient and stable wireless charging system suitable for pressurized lithium batteries, which is characterized by including a transmitter and a receiver.

[0028] The transmitter includes a power supply battery, a primary-side controller, a primary-side DC-DC converter, an inverter, a primary-side compensation network, and a primary-side coupler.

[0029] The positive and negative terminals of the power supply battery are connected to the positive and negative input ports of the primary-side DC-DC converter. The output port of the primary-side DC-DC converter is connected to the input port of the inverter. The output port of the inverter is connected to the input port of the primary-side compensation network. The output port of the primary-side compensation network is connected to the primary-side coupler. The primary-side controller controls the output voltage of the primary-side DC-DC converter through the PWM duty cycle, that is, it performs maximum efficiency tracking through the input voltage of the inverter of the wireless charging system.

[0030] The receiving end includes a pressure-bearing lithium battery, a secondary-side controller, a secondary-side DC-DC converter, a rectifier, a secondary-side compensation network, and a secondary-side coupler;

[0031] The output port of the secondary-side coupler is connected to the input port of the secondary-side compensation network. The output port of the secondary-side compensation network is connected to the input port of the rectifier. The high-frequency AC power is converted into DC power after passing through the rectifier. The output port of the rectifier is connected to the input port of the secondary-side DC-DC converter. The positive and negative output ports of the secondary-side DC-DC converter are connected to the positive and negative terminals of the pressurized lithium battery.

[0032] The primary and secondary couplers are coupled after being connected at the transmitting and receiving ends, and wireless power is transmitted between them through electromagnetic induction generated by high-frequency alternating current.

[0033] The secondary-side DC-DC converter controls the output current and voltage according to the load requirements of the pressurized lithium battery. That is, under the control of the secondary-side controller, the secondary-side DC-DC converter generates the voltage or current required by the pressurized lithium battery to replenish the energy of the pressurized lithium battery.

[0034] The primary-side DC-DC converter uses the aforementioned efficient and stable wireless charging method to achieve maximum efficiency tracking of the wireless charging system and find the optimal output voltage selection value.

[0035] Furthermore, the inverter's drive signal is constant, with a duty cycle of 50% and a phase shift angle of 180°.

[0036] The concept and principle of this invention:

[0037] To address the problems existing in current technologies, the research team conducted an in-depth analysis and discovered that parameters such as the internal resistance and actual usable charge of pressure-bearing lithium batteries change with pressure. Currently, there is no wireless charging method that considers the influence of pressure. Therefore, this invention establishes a parameter library for pressure-bearing lithium batteries under different pressures in advance, including the equivalent load resistance R. Li Actual usable charge C i During charging, the system first determines the stable output voltage range of the primary-side DC-DC converter based on the influence of pressure on battery parameters, then obtains the optimal efficiency operating point for charging and determines whether it is fully charged.

[0038] In the efficient and stable control of charging efficiency, the traditional perturbation-observation method has a high time complexity of O(n), resulting in long computation time, slow maximum efficiency tracking, and the appearance of a three-point oscillation in the final stage. This is not conducive to the rapid tracking of the maximum efficiency point. Furthermore, the theoretical optimum found by the perturbation-observation method is in a three-point oscillation region near the actual optimum. Therefore, the choice of the perturbation step size ΔV requires a trade-off between convergence speed and oscillation, which is detrimental to system stability. Figure 2As shown, increasing the perturbation step size ΔV can improve the maximum efficiency tracking speed, but the final three-point oscillation region will be very large; decreasing the perturbation step size ΔV can shrink the three-point oscillation region, but it will significantly increase the maximum efficiency tracking time. The specific operating mechanism of maximum efficiency tracking using the existing perturbation observation method in the wireless charging system is as follows:

[0039] First, under the control of the primary-side DC-DC converter (i.e., buck-boost converter), the receiving end maintains a constant current or voltage value required by the load. At this time, the output power P of the receiving end... out The voltage remains unchanged; then, the output voltage of the primary-side DC-DC converter is adjusted based on the perturbation observation algorithm, when the output power of the battery (which is also the input power P of the wireless charging system) is detected. in When the input voltage reaches its minimum, the overall system efficiency reaches its maximum. When the system is in regions A and C, the inverter input voltage can be increased or decreased by adjusting the perturbation step size ΔV, thereby continuously reducing the input power P. in When the system enters area B, V in The states become P2 and P min The three-point oscillation phase between point P4 and point P4 represents the optimal inverter input voltage for maximum efficiency. During operation, the change in inverter input voltage is controlled by the duty cycle of the primary-side DC-DC converter, using the fixed-step perturbation observation method described in CN111509865B. It is evident that to avoid the amplitude of the final three-point oscillation phase, the perturbation step size needs to be reduced; conversely, to improve the maximum efficiency tracking speed, the perturbation step size needs to be increased. Therefore, the selection of the perturbation step size requires a trade-off between oscillation amplitude and tracking speed, which is detrimental to system stability.

[0040] Therefore, to improve the speed of tracking the maximum efficiency point, this invention employs an improved perturbation-observation-golden section algorithm to achieve fast maximum efficiency tracking. First, the current solution is compared not only with the previous solution but also with the next solution. If the current solution is superior to both the previous and next solutions, the interval containing the optimal solution can be determined. Second, maximum efficiency tracking is performed using the golden section search algorithm. The time complexity of the golden section search algorithm is typically O(log n), where n is the dimension of the solution space. Since the dimension of the solution space is usually greater than 1, O(log n) < O(n). Therefore, the perturbation-observation-golden section method can improve the speed of maximum efficiency tracking to a certain extent, thereby improving the charging efficiency of the entire system.

[0041] In the wireless charging method provided by this invention, the secondary-side DC-DC converter is used to regulate the output to maintain a constant output voltage V required by the load. out Or the constant output current I required by the load outThe input voltage V of the primary-side coupler in The control method involves iterative adjustment (decrease or increase) solely by the primary-side DC-DC converter, using an improved disturbance detection-golden section algorithm, until the output power of the input battery (i.e., the input power P of the wireless power transfer system) is reached. in Reaching the minimum point. For a given output voltage or output current, reaching the minimum input power operating point is equivalent to reaching the maximum energy efficiency operating point (system efficiency η = P). out / P in So when P out P remains unchanged in (When η is at its minimum, it is at its maximum). Throughout the entire operation, the inverter's drive signal remains constant, with a duty cycle of 50% and a phase shift angle of 180°, to better ensure that the system is in a soft-switching state.

[0042] The advantages of this invention are:

[0043] 1. The transmitting end of the wireless charging system of the present invention includes a power supply battery, a primary-side controller, a primary-side DC-DC converter, an inverter, a primary-side compensation network, and a primary-side coupler; the receiving end includes a pressurized lithium battery, a secondary-side controller, a secondary-side DC-DC converter, a rectifier, a secondary-side compensation network, and a secondary-side coupler. Furthermore, the secondary-side DC-DC converter controls the output current and voltage according to the load requirements of the pressurized lithium battery, while the primary-side DC-DC converter uses the improved disturbance detection-golden section algorithm proposed in this invention to quickly achieve maximum efficiency tracking of the wireless charging system. Conventional disturbance observation only requires comparing the current solution k with the previous solution k-1, thus leading to... Figure 2 The final stage of the three-point oscillation is shown in the range B. In the improved perturbation observation in this invention, the current solution k needs to be compared not only with the previous solution k-1, but also with the next solution k+1. After determining the obtained interval, the golden section method is used to optimize the interval. Since the golden section method has uniqueness and low time complexity, it can quickly and efficiently track the problem and avoid the three-point oscillation.

[0044] 2. The perturbation observation-golden section wireless charging method proposed in this invention, compared to the simple perturbation observation method, can achieve rapid maximum efficiency tracking of the system under no-communication conditions and avoids the three-point oscillation inherent in the perturbation observation method. Furthermore, because no communication is required, it avoids the attenuation of electromagnetic waves caused by differences in underwater environmental temperature, salinity, and conductivity, which leads to long communication system delays and poor stability. This reduces the cost, size, and complexity of the underwater wireless charging system and improves its stability. In addition, since the proposed method does not involve mutual inductance, it is to some extent unaffected by the docking conditions on the system's power transmission and achieves maximum efficiency transmission under such docking conditions; therefore, it remains effective even in cases of coupler misalignment.

[0045] 3. The wireless charging method for pressurized lithium batteries proposed in this invention, compared with conventional wireless charging methods, takes into account the influence of pressure on the battery load internal resistance, actual usable charge, etc., and improves the accuracy of tracking the optimal efficiency operating point and judging the charging state. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the LCC-S compensated wireless charging system without communication proposed in this invention.

[0047] Figure 2 This describes the operating mechanism of the current fixed-step maximum efficiency tracking perturbation observation method in wireless charging systems.

[0048] Figure 3 This is a flowchart of the wireless charging method of the present invention;

[0049] Figure 4 The relationship between the system efficiency of the present invention and the output voltage range of the primary-side DC-DC converter is shown; (a) is case A, (b) is case B, and (c) is case C.

[0050] Figure 5 This invention improves the optimal solution interval iteration process during the perturbation observation phase;

[0051] Figure 6 This describes the iterative calculation process of the golden section search stage in this invention;

[0052] Figure 7 To compare the system efficiency using the perturbation-observation-golden section method and without this method;

[0053] Figure 8 For comparison of the perturbation observation-golden section method of this invention with the traditional perturbation observation method, (a) load resistance R = 7.5Ω; (b) load resistance R = 12.5Ω; Detailed Implementation

[0054] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments:

[0055] To achieve efficient and stable charging control under pressure, the wireless charging method for pressure-bearing lithium batteries proposed in this invention employs a perturbation-observation-golden section algorithm to determine the optimal efficiency operating point, achieving stable tracking of maximum charging efficiency. The method flowchart is shown below. Figure 3 As shown, the process includes three steps: determining the stable output voltage range of the primary-side DC-DC converter, determining the optimal efficiency operating point, and determining whether the battery is fully charged. The specific steps are as follows.

[0056] Step 1: Determine the stable output voltage range of the primary-side DC-DC converter

[0057] Obtain the current SOC value (SOC0) and equivalent load resistance (R) of the pressure-bearing lithium battery under different pressures. Li And the actual usable charge C of a pressure-bearing lithium battery with SOC=1 under different pressures. i ;

[0058] The SOC value mentioned above refers to the amount of electricity that a battery can release at a certain temperature and discharge rate when it is not damaged.

[0059] Generally, SOC is expressed as the percentage of charge that the battery can still release in its rated capacity, as shown in formula (1).

[0060]

[0061] In the formula, C remain C represents the remaining charge of a battery at a given discharge rate. N This is the total charge of the battery under normal pressure, i.e., the rated capacity of the battery;

[0062] Typically, when using pressurized lithium batteries, a battery management system (BMS) is used for real-time management, which can directly obtain the current SOC value of the pressurized lithium battery (SOC0).

[0063] Charging experiments were conducted on a pressure-bearing lithium battery under different pressures, and a charging voltage V was set. out And based on the BMS measurement of the battery charging current I i The equivalent load resistance R of the pressurized lithium battery is calculated according to formula (2). Li Finally, the equivalent load resistance of the pressure-bearing lithium battery under different pressures was obtained;

[0064]

[0065] Meanwhile, discharge experiments were conducted on a pressure-bearing lithium battery with SOC=1 under different pressures, and the actual usable charge C released by the battery when it was completely discharged was recorded. i Finally, the actual usable charge of the pressure-bearing lithium battery under different pressures was obtained;

[0066] Step 1.2: Based on the equivalent load resistance R under different pressures Li The battery charging power P set by the wireless charging system out The voltage gain G set by the wireless charging system determines the stable output voltage range [V] suitable for the primary-side DC-DC converter of the pressurized lithium battery. inmin V inmax Specifically:

[0067] First, calculate the charging power P using formula (3). out Equivalent load resistance R under different pressures Li The charging voltage V required by the system at that time out This refers to the output voltage of the wireless charging system.

[0068]

[0069] Secondly, the input voltage V of the wireless charging system inverter is calculated using formula (4). in That is, the output voltage of the primary-side DC-DC converter;

[0070]

[0071] Finally, the calculated minimum and maximum values ​​are selected to determine the stable output voltage range of the primary-side DC-DC converter as [V]. inmin V inmax ].

[0072] Step 2: Determine the optimal efficiency operating point

[0073] Step 2.1: Existence determination stage of the optimal solution

[0074] Since the stable output voltage range of the primary-side DC-DC converter is a finite interval, this interval may be to the left of the optimal efficiency point, to the right of the optimal efficiency point, or may include the optimal efficiency point, such as... Figure 4 As shown. Therefore, it is necessary to determine whether the range of the primary-side DC-DC converter output voltage contains the optimal solution before performing maximum efficiency tracking.

[0075] In the optimal solution existence determination stage, based on the stable output voltage range of the primary-side DC-DC converter determined in step 1, the minimum resolution of the primary-side DC-DC converter output voltage is used as the perturbation step size ΔV. The primary-side DC-DC converter starts from the maximum output voltage V(1)=V inmax Initially, decrease twice with the minimum resolution, i.e., V(2) = V inmax -ΔV and V(3)=V(2)-ΔV, and calculate the corresponding input power P respectively. in (1) P in (2) and P in (3). If P in (1) <P in (2) <P in (3), that is, belonging to Figure 4 In case (a) A, the maximum output voltage V of the primary-side DC-DC converter is... inmax If the system reaches its optimal efficiency point, the maximum efficiency tracking ends, and the process proceeds to step 3; otherwise, proceed to step 2.2.

[0076] Step 2.2: Improved Disturbance Observation Phase

[0077] In the improved perturbation observation phase, this invention improves the perturbation observation algorithm, making the current solution P... in(k) Not only must it be related to the previous solution P in(k-1) The comparison also needs to be made with the subsequent solution P. in(k+1) Comparison. To improve the speed of maximum efficiency tracking, the step size of the voltage change can be taken as a larger value, i.e., V. (k) =V (k-1) -n*ΔV, where ΔV is the minimum resolution of the output voltage of the primary-side DC-DC converter, and n*ΔV is ΔV', ΔV'=(V inmax -V inmin ) / 10, then n=[(V inmax -V inmin ) / 10] / ΔV.

[0078] In the improved disturbance observation phase, if the relationship between the system efficiency and the output voltage range of the primary-side DC-DC converter belongs to... Figure 4 Case (b) B in the above. In this case, if P in (k+1)>P in (k) <P in (k-1), the optimal solution is located in the interval [V(k+1), V(k-1)], proceed to step 2.3;

[0079] If P in (k+1)>P in (k)≥P in(k-1), the optimal solution is located in the interval [V(k), V(k-1)], proceed to step 2.3;

[0080] Figure 5 This shows the iterative process of finding the optimal solution interval in the improved perturbation observation stage. During the search process, if P always exists... in (k+1) <P in (k) <P in (k-1), until V(k+1)≤V inmin That is, belongs to Figure 4 In case (c) C, the minimum output voltage V of the primary-side DC-DC converter is... inmin The optimal output voltage value for system efficiency is selected, and maximum efficiency tracking is completed. Proceed to step 3.

[0081] Step 2.3: Golden Ratio Search Phase

[0082] After improving the perturbation observation stage, the interval where the optimal solution exists was obtained. The next step is to use the golden section search algorithm to find the optimal solution.

[0083] Golden section search is an exact line search algorithm. When using the golden section search method, the second and third points constitute the golden section point of the initial interval, such as... Figure 6 As shown, when the optimal solution interval is from the first point to the third point, the second point is exactly the golden section point of the new interval; when the optimal solution interval is from the second point to the fourth point, the third point is exactly the golden section point of the new interval. Therefore, the golden section point of the initial interval can be reused in the next iteration, greatly reducing the number of trials.

[0084] This invention provides a highly efficient and stable wireless charging method that enables faster maximum efficiency tracking. This is because, in the improved perturbation observation phase, the step size of the voltage change can be larger, and the time complexity of the golden section search algorithm is lower than that of the perturbation observation method. Furthermore, the proposed perturbation observation-golden section method for maximum efficiency tracking can effectively avoid the three-point oscillation inherent in the perturbation observation method.

[0085] Step 3: Determine if the pressure-bearing lithium battery is fully charged.

[0086] Using the optimal output voltage selected in step 2 as the input voltage, the pressurized lithium battery is charged, and the SOC value of the pressurized lithium battery is acquired in real time during the charging process. t Until SOC t =1 indicates that the pressurized lithium battery is fully charged and charging has stopped; where,

[0087]

[0088] In the formula, t is the charging time, and It Let C be the charging current at time t. N C represents the total charge of the battery under normal pressure, and ΔC represents the error in the actual usable charge of the battery due to pressure changes. i The appropriate value can be selected based on the pressure borne by the pressure-bearing lithium battery, and then ΔC = C i -C N The difference between the actual usable charge of the battery under different pressures and the total charge of the battery under normal pressure was calculated.

[0089] Figure 7 The figure shows the system efficiency as a function of load resistance, coupling coefficient, and whether or not the perturbation-observation-golden section algorithm is used. It can be seen that the system efficiency decreases with increasing load resistance, because the efficiency of the wireless charging system is related to the load resistance. When the coupling coefficient k is 0.45 or 0.50, the system efficiency using the perturbation-observation-golden section algorithm is higher than that without it, thus verifying that the perturbation-observation-golden section algorithm improves system efficiency. Furthermore, it can be demonstrated that the proposed method remains effective even when the coupling coefficient changes (i.e., coupler offset).

[0090] In the perturbation-observation-golden section algorithm, during the optimal solution existence determination stage, the voltage V... in The step size of the change is the same as that of the traditional P&O method (Perturb and Observe), i.e., ΔV, where ΔV is the minimum output resolution of the primary-side DC-DC converter. However, in the improved ramp-up phase, the voltage V... in The step size of the change is taken as (V) inmax -V inmin ) / 10 to accelerate the speed of tracking with maximum efficiency.

[0091] Figure 8 The input power P is shown for the perturbation observation-golden section and conventional perturbation observation methods under coupling coefficients k = 0.45 and 0.50 and load resistance R = 7.5 and 12.5. in The curve showing the relationship between the number of iterations and the number of iterations.

[0092] from Figure 8 As can be clearly seen in (a) and (b), traditional perturbation observation methods exhibit three-point oscillations in the final stage, while the perturbation observation-golden section method of this invention can effectively avoid oscillations. Furthermore, in Figure 8 Under the same number of iterations, the perturbation observation-golden section method has P in The value is smaller than that of traditional perturbation observation methods, which means it is more efficient.

[0093] In summary, the wireless charging method proposed in this invention, compared to traditional wireless charging methods, is the first to use a pressurized lithium battery as the charging target, achieving rapid and maximum efficiency tracking of the system under conditions without communication. It also avoids the attenuation of electromagnetic waves caused by differences in underwater environmental temperature, salinity, and conductivity, which leads to long communication system delays and poor stability. This reduces the cost, size, and complexity of the underwater wireless charging system while improving its stability. Furthermore, since the proposed method does not involve mutual inductance, it remains effective even in cases of coupler misalignment.

Claims

1. A highly efficient and stable wireless charging method suitable for pressure-bearing lithium batteries, characterized in that, Includes the following steps: Step 1: Determine the stable output voltage range of the primary-side DC-DC converter Step 1.1: Obtain the current SOC value (SOC0) and equivalent load resistance (R) of the pressure-bearing lithium battery under different pressures. Li And the actual usable charge C of a pressure-bearing lithium battery with SOC=1 under different pressures. i ; Step 1.2: Based on the equivalent load resistance R under different pressures Li The battery charging power P set by the wireless charging system out The voltage gain G set by the wireless charging system determines the stable output voltage range [V] suitable for the primary-side DC-DC converter of the pressurized lithium battery. inmin V inmax ]; Step 2: Determine the optimal efficiency operating point Step 2.1: Existence determination stage of the optimal solution Based on the stable output voltage range of the primary-side DC-DC converter determined in step 1, from the maximum output voltage V inmax Initially, decrease the value twice using its minimum resolution, and take V(1) = V inmax V(2)=V inmax -ΔV and V(3) = V(2) -ΔV are used as input voltages, and the corresponding input power P is calculated respectively. in (1) P in (2) and P in (3); where ΔV is the minimum resolution of the output voltage of the primary-side DC-DC converter; If P in (1) <P in (2) <P in (3) Then the maximum output voltage V of the primary side DC-DC converter inmax Select the optimal output voltage value for system efficiency. Maximum efficiency tracking ends. Proceed to step 3. Otherwise, proceed to step 2.2; Step 2.2: Improved Disturbance Observation Phase Within the stable output voltage range of the primary-side DC-DC converter, the output voltages are arranged in descending order (V). inmax -V inmin The input voltage is successively decreased by step size ΔV', using V(k-1)=V(k-2)-ΔV', V(k)=V(k-1)-ΔV', and V(k+1)=V(k)-ΔV' as input voltages, and the corresponding input power P is calculated for each. in (k-1), P in (k) and P in (k+1); k takes values ​​from 2 to 9, and during the iteration process: If P in (k+1)>P in (k) <P in If (k-1), then the optimal output voltage range for system efficiency is [V(k+1), V(k-1)], proceed to step 2.3; If P in (k+1)>P in (k)≥P in If (k-1), then the optimal output voltage range for system efficiency is [V(k), V(k-1)], proceed to step 2.3; If P always exists in (k+1) <P in (k) <P in (k-1), until V(k+1)≤V inmin Then the minimum output voltage V of the primary-side DC-DC converter inmin Select the optimal output voltage value for system efficiency. Maximum efficiency tracking ends. Proceed to step 3. Step 2.3: Golden Ratio Search Phase Using the golden section search algorithm, the optimal output voltage value is selected within the range of the optimal output voltage selected in step 2.2, and then proceed to step 3; Step 3: Determine if the pressure-bearing lithium battery is fully charged. Using the optimal output voltage selected in step 2 as the input voltage, the pressurized lithium battery is charged, and the SOC value of the pressurized lithium battery is acquired in real time during the charging process. t Until SOC t =1 indicates that the pressurized lithium battery is fully charged and charging has stopped; where, In the formula, t is the charging time, and I t Let C be the charging current at time t. N ΔC represents the total charge of the battery under normal pressure, and ΔC represents the error in the actual usable charge of the battery due to pressure changes. ΔC = C i -C N .

2. A high-efficiency and stable wireless charging system suitable for pressure-bearing lithium batteries, characterized in that: Includes the transmitter and receiver; The transmitter includes a power supply battery, a primary-side controller, a primary-side DC-DC converter, an inverter, a primary-side compensation network, and a primary-side coupler. The positive and negative terminals of the power supply battery are connected to the positive and negative input ports of the primary-side DC-DC converter. The output port of the primary-side DC-DC converter is connected to the input port of the inverter. The output port of the inverter is connected to the input port of the primary-side compensation network. The output port of the primary-side compensation network is connected to the primary-side coupler. The primary-side controller controls the output voltage of the primary-side DC-DC converter through the PWM duty cycle. The receiving end includes a pressure-bearing lithium battery, a secondary-side controller, a secondary-side DC-DC converter, a rectifier, a secondary-side compensation network, and a secondary-side coupler; The output port of the secondary-side coupler is connected to the input port of the secondary-side compensation network. The output port of the secondary-side compensation network is connected to the input port of the rectifier. The output port of the rectifier is connected to the input port of the secondary-side DC-DC converter. The positive and negative output ports of the secondary-side DC-DC converter are connected to the positive and negative terminals of the pressurized lithium battery. The primary and secondary couplers are coupled after being connected at the transmitting and receiving ends, and wireless power is transmitted between them through electromagnetic induction generated by high-frequency alternating current. The secondary-side DC-DC converter controls the output current and voltage according to the load requirements of the pressurized lithium battery; The primary-side DC-DC converter uses the efficient and stable wireless charging method described in claim 1 to achieve maximum efficiency tracking of the wireless charging system and find the optimal output voltage selection value.

3. The wireless charging system according to claim 2, characterized in that: The inverter has a constant drive signal, a duty cycle of 50%, and a phase shift angle of 180°.

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