A DC-DC power module efficiency self-optimization method and system

Abstract

The application provides a DC-DC power module efficiency self-optimization method and system, power distribution constraint conditions in a current operation condition of a power system are determined through real-time total power requirements of the power system; a mapping relationship between output power and operation efficiency of each DC-DC power module is established based on operation state parameters of each DC-DC power module, and then optimal target power values of each DC-DC power module that maximize overall operation efficiency are determined on the premise of meeting the power distribution constraint conditions; power adjustment instructions are sent to each DC-DC power module according to the optimal target power values to control each DC-DC power module to output corresponding power. By using the scheme of the application, power distribution can be dynamically optimized based on operation state sensing and efficiency characteristic modeling to improve overall system efficiency on the premise of ensuring stable operation of each module.

Description

Technical Field

[0001] This application relates to the field of efficiency self-optimization technology, and more specifically, to a method and system for self-optimizing the efficiency of a DC-DC power module. Background Technology

[0002] Efficiency self-optimization refers to the technical means by which a system automatically adjusts its internal operating parameters based on its real-time operating status to maintain the overall system efficiency at an optimal level. Its core lies in establishing a quantitative relationship between system operating status and efficiency, and forming a closed-loop control process through real-time detection and dynamic adjustment.

[0003] With the increasing demands for power supply capacity and reliability in applications such as data centers, communication base stations, and electric vehicles, parallel connection of multiple DC-DC power modules to form high-power power supply systems has become the mainstream technical solution. Parallel architecture improves system capacity and fault tolerance through power sharing and redundancy design. However, the core challenge when multiple modules work together is that the conversion efficiency of each module exhibits a non-linear distribution under different load conditions, with significant efficiency differences generally existing between light and heavy load regions. Existing technologies often employ fixed-ratio current sharing strategies or simple master-slave allocation strategies, failing to dynamically adjust the power allocation scheme of each module according to load changes, resulting in the system operating in a non-optimal efficiency range for extended periods. Some efficiency optimization schemes treat the efficiency of each module as a static parameter, ignoring the dynamic characteristics of efficiency changes with operating conditions such as load rate, input voltage, and temperature. They lack systematic modeling of the coupling relationship between overall system efficiency and module power allocation, making it difficult to achieve globally optimal power allocation. Furthermore, the methods for detecting operating conditions and constructing constraints are relatively crude and cannot adapt to complex operating conditions with frequent load fluctuations or significant differences in module performance. Therefore, how to dynamically optimize power allocation based on operational status awareness and efficiency characteristic modeling to improve the overall system efficiency, while ensuring the stable operation of each module, has become a problem faced by the industry. Summary of the Invention

[0004] This application provides a method and system for self-optimizing the efficiency of DC-DC power modules. Under the premise of ensuring the stable operation of each module, it can dynamically optimize power allocation based on the perception of operating status and efficiency characteristic modeling to improve the overall efficiency of the system.

[0005] In a first aspect, this application provides a method for self-optimizing the efficiency of a DC-DC power module, applicable to a power system comprising multiple DC-DC power modules connected in parallel. The method includes the following steps: Real-time detection of the total power demand of the power system and the operating status parameters of each DC-DC power module; Based on the real-time total power demand and the power output capability of each DC-DC power module, determine the power allocation constraints under the current operating conditions of the power system. Based on the efficiency characteristics data and operating status parameters of each DC-DC power module across the full power operating range, a mapping relationship between the output power and operating efficiency of each DC-DC power module is established. With the goal of maximizing the overall operating efficiency of the power system, and based on the mapping relationship, the optimal target power value of each DC-DC power module that maximizes the overall operating efficiency is determined under the premise of satisfying the power allocation constraints. According to the optimal target power value, a power adjustment command is sent to each DC-DC power module to control each DC-DC power module to output the corresponding power.

[0006] In some embodiments, the specific components include: the operating status parameters include the output voltage, output current, module temperature, and switching frequency of each DC-DC power module, as well as the input voltage and input current of each DC-DC power module.

[0007] In some embodiments, real-time detection of the total power demand of the power system and the operating status parameters of each DC-DC power module specifically includes: The total output voltage and total output current of the power system are collected in real time by voltage and current sensors installed at the total output terminal of the power system, and the real-time total power demand is determined based on the total output voltage and total output current. The operating status parameters of each DC-DC power module are obtained by collecting the output voltage and current, and input voltage and current of each DC-DC power module through voltage sampling circuits and current sampling circuits set at the output / input terminals of each DC-DC power module, respectively; collecting the module temperature through temperature sensors set inside each DC-DC power module; and obtaining the current switching frequency by reading the pulse width modulation drive signal of each DC-DC power module.

[0008] In some embodiments, determining the power allocation constraints under the current operating conditions of the power system based on the real-time total power demand and the power output capability of each DC-DC power module specifically includes: Obtain the power output capability of each DC-DC power module under the current operating status parameters; Based on the power output capability of each DC-DC power module, determine the available power range of each DC-DC power module; Based on the real-time total power demand, configure the sum of the allocated power of each DC-DC power module to equal the real-time total power demand; The power allocation constraint is defined as follows: the sum of the allocated power of each DC-DC power module equals the real-time total power demand, and the allocated power of each DC-DC power module is within the corresponding available power range.

[0009] In some embodiments, establishing a mapping relationship between the output power and operating efficiency of each DC-DC power module based on the efficiency characteristic data and operating state parameters of each DC-DC power module across its full power operating range specifically includes: Obtain efficiency characteristic data for each DC-DC power module under multiple preset power operating points, corresponding to different module temperatures and input voltage conditions; Using the output power and operating state parameters of each DC-DC power module as input variables, the efficiency characteristic data is fitted to obtain the dynamic efficiency characteristic curve of each DC-DC power module under any combination of output power and input voltage. The mapping relationship between the output power and operating efficiency of each DC-DC power module is determined based on the dynamic efficiency characteristic curve.

[0010] In some embodiments, with the goal of maximizing the overall operating efficiency of the power system, and based on the mapping relationship, determining the optimal target power value of each DC-DC power module that maximizes the overall operating efficiency, while satisfying the power allocation constraints, specifically includes: Based on the mapping relationship between the output power and operating efficiency of each DC-DC power module, the estimated input power values ​​under different power allocation combinations of each DC-DC power module are calculated respectively. The overall operating efficiency of the power system under each power allocation combination is determined based on the estimated values ​​of each input power. Under the condition that the sum of the power allocated to each DC-DC power module is equal to the real-time total power demand and the power allocated to each DC-DC power module does not exceed its respective power output capability, the power allocation value of each DC-DC power module that maximizes the overall operating efficiency of the power system is determined as the optimal target power value of the corresponding DC-DC power module.

[0011] In some embodiments, sending power adjustment commands to each DC-DC power module according to the optimal target power value to control each DC-DC power module to output the corresponding power specifically includes: The optimal target power value of each DC-DC power module is compared with the current actual output power of each DC-DC power module to determine the power adjustment amount of each DC-DC power module. Based on the power adjustment amount of each DC-DC power module, a corresponding power adjustment command is generated and sent to the drive control terminal of the corresponding DC-DC power module to adjust the switching duty cycle of each DC-DC power module so that the actual output power of each DC-DC power module follows the optimal target power value.

[0012] Secondly, this application provides a DC-DC power module efficiency self-optimization system, applied to a power system comprising multiple DC-DC power modules connected in parallel, the DC-DC power module efficiency self-optimization system comprising: The acquisition module is used to detect the real-time total power demand of the power system and the operating status parameters of each DC-DC power module in real time. The processing module is used to determine the power allocation constraints of the power system under the current operating conditions based on the real-time total power demand and the power output capability of each DC-DC power module. The processing module is also used to establish a mapping relationship between the output power and operating efficiency of each DC-DC power module based on the efficiency characteristic data of each DC-DC power module in the full power operating range and various operating status parameters. The processing module is further configured to determine the optimal target power value of each DC-DC power module that maximizes the overall operating efficiency of the power system, based on the mapping relationship and under the premise of satisfying the power allocation constraints, with the goal of maximizing the overall operating efficiency of the power system. The execution module is used to send power adjustment commands to each DC-DC power module according to the optimal target power value, so as to control each DC-DC power module to output the corresponding power.

[0013] Thirdly, this application provides a computer device, the computer device including a memory and a processor, the memory storing code, and the processor being configured to acquire the code and execute the above-described DC-DC power module efficiency self-optimization method.

[0014] Fourthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for self-optimizing the efficiency of a DC-DC power module.

[0015] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects: The DC-DC power module efficiency self-optimization method and system provided in this application firstly detects the real-time total power demand of the power system and the operating status parameters of each DC-DC power module in real time. Based on the real-time total power demand and power output capability, power allocation constraints are determined, incorporating the available power range of each module into the limits. This ensures that the optimization solution always remains within the stable operating capability boundaries of each module, fundamentally avoiding the risk of system instability caused by power allocation exceeding the module's carrying capacity. It also effectively solves the safety hazards caused by crude operating status detection methods and imperfect constraint construction methods. Based on efficiency characteristic data and operating status parameters, a mapping relationship between output power and operating efficiency is established, extending efficiency modeling from static parameters to dynamic functions. This characterizes the nonlinear characteristics of efficiency changing with load rate, input voltage, and temperature, overcoming the inherent defect of treating efficiency as a fixed parameter in existing technologies. With the goal of maximizing overall system efficiency, the optimal target power value is solved under constraints, establishing a global coupling optimization mechanism between overall system efficiency and power allocation of each module. This solves the problem that traditional current sharing or master-slave strategies cannot achieve globally optimal efficiency allocation and overcomes the problem that some schemes only perform local optimization of single-module efficiency. Based on the optimal target power value, adjustment commands are sent to control the output power of each module accordingly. The optimization results are applied in a closed loop to the system operation, enabling the power system to continuously track the optimal efficiency operating point under complex operating conditions such as frequent load fluctuations or large differences in module performance. This truly realizes the engineering implementation and practical closed-loop control of efficiency self-optimization. Using the solution proposed in this application, power allocation can be dynamically optimized based on operating status perception and efficiency characteristic modeling to improve the overall system efficiency, while ensuring the stable operation of each module. Attached Figure Description

[0016] Figure 1 This is an exemplary flowchart of a DC-DC power module efficiency self-optimization method according to some embodiments of this application; Figure 2 This is an exemplary flowchart illustrating the determination of mapping relationships according to some embodiments of this application; Figure 3 This is a schematic diagram of a power system structure consisting of multiple parallel DC-DC power modules according to some embodiments of this application; Figure 4 This is a schematic diagram of the structure of a DC-DC power module efficiency self-optimization system according to some embodiments of this application; Figure 5 This is a schematic diagram of the structure of a computer device that implements a method for self-optimizing the efficiency of a DC-DC power module according to some embodiments of this application. Detailed Implementation

[0017] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0018] refer to Figure 1 The figure is an exemplary flowchart of a DC-DC power module efficiency self-optimization method according to some embodiments of this application. The DC-DC power module efficiency self-optimization method mainly includes the following steps: In step 101, the real-time total power demand of the power system and the operating status parameters of each DC-DC power module are detected in real time.

[0019] In some embodiments, real-time detection of the total power demand of the power system and the operating status parameters of each DC-DC power module can be achieved by the following steps: The total output voltage and total output current of the power system are collected in real time by voltage and current sensors installed at the total output terminal of the power system, and the real-time total power demand is determined based on the total output voltage and total output current. The operating status parameters of each DC-DC power module are obtained by collecting the output voltage and current, and input voltage and current of each DC-DC power module through voltage sampling circuits and current sampling circuits set at the output / input terminals of each DC-DC power module, respectively; collecting the module temperature through temperature sensors set inside each DC-DC power module; and obtaining the current switching frequency by reading the pulse width modulation drive signal of each DC-DC power module.

[0020] It should be noted that the real-time total power demand in this application is used to characterize the total output power that the power supply system needs to provide to the load at the current moment. The operating status parameters of each DC-DC power module are a set of physical quantities used to characterize the operating voltage, operating current, operating temperature, and switching frequency of each DC-DC power module at the current moment. The operating status parameters include the output voltage, output current, module temperature, and switching frequency of each DC-DC power module, as well as the input voltage and input current of each DC-DC power module.

[0021] The specific implementation method for real-time detection of the total power demand of the power system is as follows: A voltage sensor and a current sensor are installed at the total output terminal of the power system. The voltage sensor senses the voltage signal at the total output terminal of the power system, and the current sensor senses the current signal at the total output terminal of the power system. During the operation of the power system, the voltage sensor continuously collects the real-time voltage value at the total output terminal of the power system, and the current sensor continuously collects the real-time current value at the total output terminal of the power system. The real-time voltage value and the real-time current value are multiplied to obtain the power product value. The power product value is used as the real-time total power demand of the power system at the current moment.

[0022] The specific implementation method for detecting the operating status parameters of each DC-DC power module: An output voltage sampling circuit and an output current sampling circuit are installed at the output terminals of each DC-DC power module. The output voltage sampling circuit is used to collect the voltage signal at the output terminal of the corresponding DC-DC power module, and the output current sampling circuit is used to collect the current signal at the output terminal of the corresponding DC-DC power module. An input voltage sampling circuit and an input current sampling circuit are installed at the input terminals of each DC-DC power module. The input voltage sampling circuit is used to collect the voltage signal at the input terminal of the corresponding DC-DC power module, and the input current sampling circuit is used to collect the current signal at the input terminal of the corresponding DC-DC power module. A temperature sensor is installed inside each DC-DC power module, close to the power switching transistor. The temperature sensor is used to sense the internal operating temperature of the corresponding DC-DC power module. During the operation of each DC-DC power module, the output voltage and output current values ​​of the corresponding DC-DC power module are collected by the output voltage sampling circuit and the output current sampling circuit, respectively. The input voltage and input current values ​​of the corresponding DC-DC power module are collected by the input voltage sampling circuit and the input current sampling circuit, respectively. The internal operating temperature of the corresponding DC-DC power module is collected by the temperature sensor. The switching frequency of the corresponding DC-DC power module at the current moment is obtained by reading the pulse width modulation drive signal of the corresponding DC-DC power module. The collected output voltage, output current, input voltage, input current, operating temperature, and switching frequency values ​​are collectively used as the operating status parameters of the corresponding DC-DC power module at the current moment.

[0023] In step 102, the power allocation constraints under the current operating conditions of the power system are determined based on the real-time total power demand and the power output capability of each DC-DC power module.

[0024] In some embodiments, determining the power allocation constraints under the current operating conditions of the power system based on the real-time total power demand and the power output capability of each DC-DC power module can be achieved through the following steps: Obtain the power output capability of each DC-DC power module under the current operating status parameters; Based on the power output capability of each DC-DC power module, determine the available power range of each DC-DC power module; Based on the real-time total power demand, configure the sum of the allocated power of each DC-DC power module to equal the real-time total power demand; The power allocation constraint is defined as follows: the sum of the allocated power of each DC-DC power module equals the real-time total power demand, and the allocated power of each DC-DC power module is within the corresponding available power range.

[0025] It should be noted that the power output capability in this application is a capability indicator used to characterize the upper and lower limits of the power that each DC-DC power module can output under the current operating state. The available power range is a continuous power interval defined by the lowest and highest allowed power values ​​of each DC-DC power module under the current operating state. The allocated power is a target parameter used to characterize the power value allocated to each DC-DC power module under the stated power allocation constraints. The power allocation constraints are a set of rules that characterize the limiting conditions that each DC-DC power module must satisfy for the allocated power.

[0026] The specific implementation method for obtaining the power output capability of each DC-DC power module under the current operating status parameters is as follows: Based on the input voltage and switching frequency of each DC-DC power module, the upper limit of the rated output power of each DC-DC power module under rated operating conditions is determined. This upper limit of rated output power is the maximum power that each DC-DC power module can stably output under standard test conditions. Next, the temperature derating factor of each DC-DC power module is determined based on its operating temperature. This is achieved by pre-calibrating experimentally or obtaining temperature derating curves or data tables provided by the module manufacturers. These curves or data tables record the allowable derating ratio of the module relative to its rated output power at different operating temperatures. During actual system operation, the real-time collected operating temperature values ​​of each module are substituted into the corresponding temperature derating curves or data tables, and the temperature derating factor of each module at the current temperature is calculated by looking up the table or using linear interpolation. This temperature derating factor characterizes the correction ratio of the upper limit of output power when the operating temperature deviates from the standard temperature. Multiplying the upper limit of the rated output power of each DC-DC power module by the corresponding temperature derating factor yields the upper limit of usable power for each DC-DC power module at the current operating temperature. Simultaneously, based on the input voltage value of each DC-DC power module and the minimum controllable duty cycle of the pulse width modulation drive signal, the minimum stable output power limit for each DC-DC power module is determined. This minimum stable output power limit is the minimum power value that each DC-DC power module can reliably output while maintaining stable voltage output and continuous operation. The upper limit of usable power and the lower limit of minimum stable output power for each DC-DC power module are used as the power output capability of each DC-DC power module under the current operating parameters.

[0027] Based on the power output capability of each DC-DC power module, the specific implementation method for determining the usable power range of each DC-DC power module is as follows: The power output capability of each DC-DC power module includes an upper limit of its usable power and a lower limit of its minimum stable output power. The lower limit of the minimum stable output power is used as the lower boundary of the module's usable power range. The upper limit of the usable power is used as the upper boundary of the module's usable power range. A continuous power interval is defined by these lower and upper boundary values, where any power value within this interval represents the stable power output of the DC-DC power module under its current state. This continuous power interval is defined as the usable power range of each DC-DC power module.

[0028] The specific implementation method for configuring the sum of the allocated power of each DC-DC power module to equal the real-time total power demand is as follows: The allocated power of each DC-DC power module is set as a variable value to be determined, with each allocated power corresponding to the power value undertaken by each DC-DC power module in the power allocation scheme. The allocated power of each DC-DC power module is added together to obtain the total allocated power value. The total allocated power value is configured to be equal to the real-time total power demand, so that the total output power of the power system accurately matches the real-time total power demand required by the load.

[0029] All the constraints determined in the preceding steps are combined as the power allocation constraints. The power allocation constraints include two conditions. The first condition is that the sum of the allocated power of each DC-DC power module equals the real-time total power demand. This condition ensures that the total output power of the power system precisely matches the load demand. The second condition is that the allocated power of each DC-DC power module is within the module's available power range; that is, each allocated power is not lower than the corresponding module's minimum stable output power lower limit and not higher than the corresponding module's available power upper limit. This condition ensures that each DC-DC power module operates within its stable output power range. The logical combination of the first and second conditions is used as the power allocation constraints.

[0030] In step 103, based on the efficiency characteristic data of each DC-DC power module in the full power operating range and each operating status parameter, a mapping relationship between the output power and operating efficiency of each DC-DC power module is established.

[0031] In some embodiments, reference Figure 2 The figure is an exemplary flowchart for determining the mapping relationship in some embodiments of this application. In this embodiment, the mapping relationship between the output power and operating efficiency of each DC-DC power module is established based on the efficiency characteristic data of each DC-DC power module in the full power operating range and various operating state parameters. This can be achieved by the following steps: In step 1031, efficiency characteristic data of each DC-DC power module under multiple preset power operating points, corresponding to different module temperatures and input voltage conditions, are obtained. In step 1032, the output power of each DC-DC power module and each operating state parameter are used as input variables to perform multidimensional surface fitting on the efficiency characteristic data, so as to obtain the dynamic efficiency characteristic curve between the output power and operating efficiency of each DC-DC power module in the full operating space. In step 1033, the mapping relationship between the output power and operating efficiency of each DC-DC power module is determined based on the dynamic efficiency characteristic curve.

[0032] It should be noted that the efficiency characteristic data in this application is a test dataset used to characterize the efficiency values ​​of each DC-DC power module under different combinations of output power, input voltage, and operating temperature. The dynamic efficiency characteristic curve is a three-dimensional spatial surface used to characterize the corresponding changes in the operating efficiency of each DC-DC power module under continuously varying output power, input voltage, and operating temperature. The mapping relationship is a functional correspondence used to characterize the one-to-one correspondence between the output power value and the operating efficiency value of each DC-DC power module under specific input voltage and operating temperature conditions.

[0033] The specific implementation method for obtaining efficiency characteristic data of each DC-DC power module under multiple preset power operating points, corresponding to different module temperatures and input voltage conditions: Efficiency characteristic tests were performed on each DC-DC power module. During the tests, the input voltage of each DC-DC power module was set to different values, covering multiple voltage levels within the rated input voltage range of each module. At each input voltage value, the output power of each DC-DC power module was controlled to reach multiple preset power operating points, covering multiple power levels from the lowest stable output power to the rated output power. At each power operating point, after the operating temperature of each DC-DC power module stabilized, the input power and output power values ​​of each module were recorded. The ratio of the output power value to the input power value was taken as the efficiency value of each DC-DC power module at that power operating point. Simultaneously, the operating temperature of each module after stable operation at the current power operating point was recorded using a temperature sensor installed inside each DC-DC power module. Following the above method, all preset input voltage values ​​and all preset power operating points are iterated to obtain the efficiency values ​​of each DC-DC power module under different combinations of input voltage values, output power values, and operating temperature values. All obtained efficiency values, along with their corresponding input voltage values, output power values, and operating temperature values, are collectively used as the efficiency characteristic data for each DC-DC power module.

[0034] Using the output power and operating parameters of each DC-DC power module as input variables, a multi-dimensional surface fitting is performed on the efficiency characteristic data to obtain the dynamic efficiency characteristic curve between the output power and operating efficiency of each DC-DC power module in the entire operating condition space. The operating status parameters include the input voltage and operating temperature values ​​of each DC-DC power module. The output power values ​​from the efficiency characteristic data are used as the first input variable, the corresponding input voltage values ​​from the efficiency characteristic data are used as the second input variable, the corresponding operating temperature values ​​from the efficiency characteristic data are used as the third input variable, and the efficiency values ​​from the efficiency characteristic data corresponding to the above three variables are used as the target output. For each DC-DC power module, all efficiency characteristic data corresponding to that module are organized according to the above variable structure to form an independent fitting sample set for that module. Using the first, second, and third input variables as input parameters and the target output as the output parameter, a multidimensional surface fitting operation is performed on all efficiency characteristic data. The multidimensional surface fitting operation is implemented using a polynomial basis function fitting method or a radial basis function interpolation fitting method based on the least squares criterion. Its core lies in minimizing the sum of squares of the deviations between the calculated efficiency value and the actual measured value at each sample point by adjusting the coefficients or basis function weights of the fitting function, thereby determining the specific mathematical expression of the fitting function. This multidimensional surface fitting operation is achieved by constructing a continuous mathematical function with output power, input voltage, and operating temperature as independent variables and efficiency as the dependent variable. Specifically, the continuous mathematical function is constructed by selecting a set of basis functions with second-order continuous differentiability, using a linear combination of these basis functions as the basic framework of the function, and solving the normal equations derived from the least squares criterion to determine the combination coefficients of each basis function, thus obtaining a uniquely determined continuous mathematical function expression. This continuous mathematical function can form a continuously changing geometric surface in a three-dimensional space composed of output power, input voltage, and operating temperature. After the continuous mathematical function is constructed, the fitting residual of the fitting function at each sample point is further calculated, and the root mean square error (RMSE) of all sample points is statistically analyzed. When the RMSE is less than a preset fitting accuracy threshold, the fitting result is deemed acceptable. When the RMSE is greater than or equal to the preset fitting accuracy threshold, the fitting operation is re-executed by increasing the number of basis functions in the basis function family or adjusting the shape parameters of the basis functions until the fitting accuracy meets the requirements. Any point on this geometric surface uniquely corresponds to an efficiency value under a specific combination of output power, input voltage, and operating temperature values, and the surface can reflect the dynamic evolution trend of the efficiency value as the three independent variables change continuously. Furthermore, this continuous mathematical function has extrapolation capabilities. For any combination of output power, input voltage, and operating temperature values ​​not included in the efficiency characteristic data, the function can output the corresponding efficiency calculation value through surface interpolation or smooth extrapolation, thereby covering all possible operating conditions of each DC-DC power module within its full power operating range.The three-dimensional continuous geometric surface obtained after fitting is used as the dynamic efficiency characteristic curve of each DC-DC power module.

[0035] The specific implementation method for determining the mapping relationship between the output power and operating efficiency of each DC-DC power module based on the dynamic efficiency characteristic curve is as follows: For each DC-DC power module, the real-time input voltage and operating temperature are obtained from the three-dimensional continuous geometric surface corresponding to the dynamic efficiency characteristic curve. On this surface, using the current real-time input voltage and operating temperature as fixed constraints, a two-dimensional cross-sectional curve is extracted, showing the efficiency value as a function of output power. This curve represents all possible efficiency values ​​corresponding to different output power values ​​under the current actual input voltage and operating temperature conditions. A correspondence rule from output power value to efficiency value is established, uniquely determining a corresponding efficiency value for any given output power value on the two-dimensional cross-sectional curve. This established rule is used as the mapping relationship between the output power and operating efficiency of the DC-DC power module under the current operating conditions. Each DC-DC power module independently performs the above extraction and rule establishment operations to obtain its own mapping relationship.

[0036] In step 104, with the goal of maximizing the overall operating efficiency of the power system, based on the mapping relationship and under the premise of satisfying the power allocation constraints, the optimal target power value of each DC-DC power module that maximizes the overall operating efficiency is determined.

[0037] In some embodiments, with the goal of maximizing the overall operating efficiency of the power system, and based on the mapping relationship, the optimal target power value of each DC-DC power module that maximizes the overall operating efficiency can be determined by the following steps, provided that the power allocation constraints are met: Based on the mapping relationship between the output power and operating efficiency of each DC-DC power module, the estimated input power values ​​under different power allocation combinations of each DC-DC power module are calculated respectively. The overall operating efficiency of the power system under each power allocation combination is determined based on the estimated values ​​of each input power. Using the power allocation of each DC-DC power module as the decision variable, the overall operating efficiency of the power system as the objective function, and the power allocation constraints as the constraints, a mathematical model for optimizing the efficiency of the power system is constructed. Within the feasible region of the efficiency optimization mathematical model, the decision variables are iteratively solved to obtain the optimal solution vector that makes the objective function reach its global maximum. The values ​​of each decision variable in the optimal solution vector are determined as the optimal target power values ​​of the corresponding DC-DC power modules.

[0038] It should be noted that the input power estimate in this application is a physical quantity used to characterize the estimated input power required for each DC-DC power module to operate under each allocated power value. Overall operating efficiency is a performance index used to characterize the ratio of the total output power to the total input power of the power system when all DC-DC power modules are operating together. Decision variables are unknown parameters used to characterize the allocated power values ​​of each DC-DC power module to be determined during the efficiency optimization process. The objective function is a mathematical expression used to characterize the mapping relationship between the overall operating efficiency of the power system and the values ​​of each decision variable. Constraints are a set of restrictive rules used to limit the range of values ​​for each decision variable, including power balance equality constraints and operating boundary inequality constraints. The efficiency optimization mathematical model is a complete mathematical programming framework used to characterize the optimization direction of maximizing or minimizing the objective function, the decision variables as the objects to be solved, and the constraints as the criteria for defining the feasible region. The feasible region is the set space used to characterize all combinations of decision variable values ​​in the efficiency optimization mathematical model that simultaneously satisfy both the power balance equality constraints and the operating boundary inequality constraints. The optimal solution vector is a complete set of vectors representing the optimal values ​​of each decision variable that maximize the objective function value within the feasible region of the efficiency optimization mathematical model. The optimal target power value is a target parameter representing the power output value of each DC-DC power module when the overall operating efficiency of the power system reaches its maximum value, while satisfying the power allocation constraints.

[0039] Based on the mapping relationship between the output power and operating efficiency of each DC-DC power module, the specific implementation methods for calculating the input power estimation values ​​under different power allocation combinations of each DC-DC power module are as follows: The allocated power value of each DC-DC power module is set as a variable. Under each power allocation combination, each DC-DC power module corresponds to an allocated power value. Substituting the allocated power value of each DC-DC power module into the mapping relationship of the corresponding module, the operating efficiency value of each DC-DC power module under its respective allocated power value is obtained. Based on the allocated power value and corresponding operating efficiency value of each DC-DC power module, the allocated power value is divided by the operating efficiency value to obtain the input power value required for each DC-DC power module to operate under that allocated power value. The input power value represents the amount of power obtained by the DC-DC power module from the input terminal to output the allocated power value. Following the above method, all possible power allocation combinations are traversed, and the input power value of each DC-DC power module under each power allocation combination is calculated. The input power values ​​of all DC-DC power modules under each power allocation combination are used as the estimated input power value of each DC-DC power module under that power allocation combination.

[0040] The specific implementation method for determining the overall operating efficiency of the power system under various power allocation combinations is based on the estimated values ​​of each input power: Each power allocation combination includes the allocated power value for each DC-DC power module and the corresponding estimated input power value. Under each power allocation combination, the allocated power values ​​of all DC-DC power modules are summed to obtain the total output power value for that power allocation combination. Under the same power allocation combination, the estimated input power values ​​of all DC-DC power modules are summed to obtain the total input power value for that power allocation combination. The total output power value is divided by the total input power value to obtain the power ratio for that power allocation combination. The power ratio represents the ratio of the total output power to the total input power of the power system under that power allocation combination. The power ratio is used as the overall operating efficiency of the power system under that power allocation combination. The overall operating efficiency of the power system under each power allocation combination is calculated in the above manner.

[0041] The following is a specific implementation method for constructing a mathematical model for optimizing the efficiency of the power system, using the allocated power of each DC-DC power module as the decision variable, the overall operating efficiency of the power system as the objective function, and the power allocation constraints as the constraints: The allocated power of each DC-DC power module is set as the decision variable to be solved. The number of these decision variables is equal to the total number of DC-DC power modules connected in parallel in the power system. The overall operating efficiency of the power system is used as the optimization objective. An objective function is constructed based on the correlation between each decision variable and the overall operating efficiency. The objective function is constructed on the following basis: for any combination of decision variable values, the estimated input power of each module can be calculated through the mapping relationship between the modules, thereby deriving the estimated total input power and total output power of the system, and finally obtaining the overall operating efficiency value under this combination. Thus, a complete mapping expression from the decision variable space to the overall operating efficiency value is established. The specific form of the objective function is to minimize the estimated total input power of the system as the optimization objective. The equivalence between the objective function and the maximization of overall operating efficiency is determined by the following principle: Under the power balance constraint that the sum of all decision variables equals the real-time total power demand, the total output power of the system is a fixed constant. Therefore, minimizing the estimated total input power of the system is mathematically equivalent to maximizing the ratio of the total output power of the system to the total input power of the system. That is, the two optimization directions point to the same optimal set of decision variables.

[0042] The power allocation constraint, which states that the sum of the allocated power of each module equals the real-time total power demand, is transformed into a power balance equation constraint. This constraint ensures that the sum of all decision variables must be strictly equal to the real-time total power demand. Specifically, this power balance equation constraint requires that the cumulative sum of all decision variable values ​​strictly match the real-time total power demand. When a DC-DC power module in the power system fails and exits operation, or when a new module is added to the parallel system, the total number of decision variables decreases or increases accordingly. Simultaneously, the real-time total power demand on the right side of the equation remains unchanged, while the constraint entries for the exited module in the operating boundary inequality constraint are automatically deleted, and the constraint entries for the newly added module are automatically added. The constraint that the allocated power of each module must be within its respective available power range is also transformed into an operating boundary inequality constraint. This constraint ensures that the value of each decision variable must be within the closed interval defined by the module's minimum stable output power value and the upper limit of its available power. In the operational boundary inequality constraints, the lower bound of each decision variable is the minimum stable output power value of the corresponding module, which is determined by the minimum power that the module can reliably output in maintaining stable voltage output and continuous operation mode. The upper bound of each decision variable is the upper limit of the available power of the corresponding module, which is determined by the maximum safe output power of the module after the current operating temperature drops. The upper and lower bounds of each decision variable are dynamically updated according to the real-time operating status parameters of each module in each real-time total power demand detection cycle. Integrating the objective function, decision variables, power balance equality constraints, and operational boundary inequality constraints as described above forms a complete efficiency optimization mathematical model. The mathematical meaning of this model is to find the combination of decision variables that maximizes the objective function within the range of decision variable values ​​that satisfy all equality and inequality constraints. The complete expression of this efficiency optimization mathematical model is: under the premise that all decision variables are greater than or equal to their corresponding lower bounds and less than or equal to their corresponding upper bounds, and the sum of all decision variables is exactly equal to the real-time total power demand, seek the combination of decision variable values ​​that minimizes the estimated total input power of the system. After obtaining the optimal decision vector by solving the mathematical model, a feasible solution verification operation must be performed. This involves substituting the values ​​of each decision variable in the optimal decision vector into the operational boundary inequality constraints of the corresponding module for verification. The verification confirms that each decision variable value is strictly within the available power range of the corresponding module, and that the deviation between the sum of all decision variable values ​​and the real-time total power demand is less than a preset numerical tolerance threshold. Only when both verifications pass is the optimal decision vector output as a valid optimization result. If the verification fails, the solution result is discarded, and a re-solution process is triggered. All the above integrated elements are then used as the efficiency optimization mathematical model.

[0043] Within the feasible region of the efficiency optimization mathematical model, the decision variables are iteratively solved to obtain the specific implementation of the optimal solution vector that makes the objective function reach its global maximum: After the efficiency optimization mathematical model is constructed, the feasible range of all decision variables is first determined based on the power balance equality constraint and the operating boundary inequality constraint. The feasible region is formed by the combinations of decision variable values ​​that satisfy all constraints. Within this feasible region, an iterative solution operation is performed on the decision variables. The specific process of this iterative solution operation is as follows: A set of initial values ​​of decision variables that satisfy all constraints is selected as the iteration starting point, and the objective function value corresponding to this starting point is calculated. Based on this, the values ​​of each decision variable are adjusted in the direction that increases the objective function value, generating new combinations of decision variable values ​​and calculating the corresponding objective function value. The newly generated objective function value is compared with the objective function value of the previous round. If the objective function value is improved, the adjustment continues in that direction; if the objective function value is not improved, the adjustment direction is changed and the search is restarted. During each adjustment process, it is verified whether the new combination of decision variable values ​​still satisfies all equality and inequality constraints. Only combinations that satisfy all constraints are retained as valid intermediate results of the iteration. When the improvement in the objective function value after multiple consecutive iterations is less than the preset convergence threshold, the iteration process is determined to have converged to the optimal solution, and the iteration operation is terminated. The combination of decision variable values ​​that maximizes the objective function value when the iteration converges is taken as the optimal solution vector.

[0044] The specific implementation method for determining the values ​​of each decision variable in the optimal solution vector as the optimal target power value of the corresponding DC-DC power module is as follows: After obtaining the optimal solution vector, a decomposition operation is performed on it. Following the order of the decision variables in the efficiency optimization mathematical model, each element in the optimal solution vector is extracted sequentially. Each extracted element value corresponds to the optimal allocated power value for a specific DC-DC power module. This element value is then used as the optimal target power value for the corresponding DC-DC power module. This extraction and mapping operation is performed on all elements until all DC-DC power modules have obtained their respective optimal target power values.

[0045] In step 105, a power adjustment command is sent to each DC-DC power module according to the optimal target power value to control each DC-DC power module to output the corresponding power.

[0046] In some embodiments, sending power adjustment commands to each DC-DC power module according to the optimal target power value to control each DC-DC power module to output the corresponding power can be achieved by the following steps: Compare the optimal target power value of each DC-DC power module with the current actual output power of each DC-DC power module, and calculate the power deviation and deviation change rate of each DC-DC power module. Based on the power deviation and the rate of change of deviation, and combined with the current input voltage value of each DC-DC power module, calculate the required drive signal adjustment for each DC-DC power module. Based on the adjustment of the drive signal of each DC-DC power module, a corresponding power adjustment command is generated and sent to the drive control terminal of the corresponding DC-DC power module to adjust the duty cycle or switching frequency of the switching transistor of each DC-DC power module, forming a power closed-loop tracking control, so that the actual output power of each DC-DC power module follows the optimal target power value.

[0047] It should be noted that the power deviation in this application is a physical quantity characterizing the power deviation between the optimal target power value and the current actual output power value of each DC-DC power module. The deviation change rate is a dynamic physical quantity characterizing the rate of change of the power deviation of each DC-DC power module relative to time. The drive signal adjustment quantity is a control parameter characterizing the magnitude of the drive signal of the power switching device required by each DC-DC power module to adjust its actual output power to approach the optimal target power value. The power adjustment command is a control command carrier that carries the value of the drive signal adjustment quantity required by each DC-DC power module and drives the power switching device to perform the corresponding power adjustment operation. The switching duty cycle is a ratio parameter characterizing the ratio of the on-time of the power switching transistor in each DC-DC power module within a complete switching cycle to the total duration of the switching cycle. The switching frequency is a frequency parameter characterizing the number of on-off switching operations performed by the power switching transistor in each DC-DC power module per unit time. Power closed-loop tracking control is a cyclic control process that continuously detects the deviation between the actual output power and the target power and adjusts the drive signal accordingly to ensure that the actual output power continuously follows the target power value.

[0048] The specific implementation method for calculating the power deviation and deviation change rate of each DC-DC power module is as follows: The optimal target power value of each DC-DC power module is compared with the current actual output power of each DC-DC power module. For each DC-DC power module, the optimal target power value is obtained. Simultaneously, the current output voltage and current values ​​are collected in real-time through output voltage and current sampling circuits at the module's output terminals. The actual output power value is obtained by multiplying the current output voltage and current values. The actual output power value is then subtracted from the optimal target power value, and the difference is taken as the module's power deviation. If the power deviation is positive, it indicates that the module's current actual output power is lower than the optimal target power value, and the output power needs to be increased to approach the optimal target power value. If the power deviation is negative, it indicates that the module's current actual output power is higher than the optimal target power value, and the output power needs to be reduced to return to the optimal target power value. If the power deviation is zero, it indicates that the module's current actual output power has reached the optimal target power value, and no power adjustment operation is required. After obtaining the power deviation value for the current control cycle, the historical power deviation value recorded in the previous control cycle for each module is read from a pre-allocated data buffer in the system memory used to record the historical power deviation values ​​of each module. If this module is performing a power adjustment operation for the first time, meaning there is no historical power deviation from the previous control cycle in the data buffer, the historical power deviation from the previous control cycle is set to zero, and this zero value is used as the historical power deviation for the initial calculation of the deviation change rate. The power deviation of the current control cycle is subtracted from the historical power deviation of the previous control cycle, and the difference is divided by the time interval between two adjacent control cycles. The quotient is used as the deviation change rate of this module. The time interval between two adjacent control cycles is a fixed control cycle duration preset by the system, determined by the system's control sampling frequency. When the deviation change rate is positive, it indicates that the power deviation is increasing over time, meaning the deviation of the actual output power from the optimal target power value is intensifying; when the deviation change rate is negative, it indicates that the power deviation is decreasing over time, meaning the actual output power is approaching the optimal target power value; when the deviation change rate is zero, it indicates that the power deviation remains constant over time, meaning the deviation between the actual output power and the optimal target power value is stable.

[0049] Based on the power deviation and deviation change rate, and combined with the current input voltage value of each DC-DC power module, calculate the specific implementation method of the required drive signal adjustment for each DC-DC power module: For each DC-DC power module, the power deviation and deviation rate of change calculated in the first step are obtained. Simultaneously, the current input voltage value is acquired in real time through the input voltage sampling circuit at the module's input terminal. The first, second, and third proportional coefficients, pre-stored in the system memory, are read. These coefficients are constant parameter values ​​determined in advance through module characteristic testing or system tuning. The power deviation is scaled according to the preset first proportional coefficient (multiplied by the power deviation), and the product is used as a proportional control component. This component is used to determine the basic adjustment direction and amplitude of the drive signal based on the current power deviation. The deviation rate of change is scaled according to the preset second proportional coefficient (multiplied by the deviation rate of change), and the product is used as a differential control component. This component is used to adjust the drive signal in advance based on the changing trend of the power deviation to suppress power overshoot. The module reads the sum of power deviations from all historical control cycles prior to the current control cycle from a pre-allocated integral accumulation buffer in the system memory. This sum is then scaled using a preset third proportional coefficient (multiplied by the coefficient), and the product is used as the integral control component. This integral control component is used to eliminate long-term accumulated static power deviations. The proportional control component, derivative control component, and integral control component are then summed to obtain the initial drive signal adjustment. Then, based on the input voltage value currently acquired by the module, a feedforward compensation correction operation is performed on the initial drive signal adjustment. Specifically, the historical input voltage value recorded by the module in the previous control cycle is obtained, and the current input voltage value is subtracted from the historical input voltage value to obtain the input voltage change. The input voltage change is scaled according to a preset fourth proportional coefficient, that is, the input voltage change is multiplied by the fourth proportional coefficient, and the product is used as the feedforward compensation correction amount. The fourth proportional coefficient is a constant parameter value determined in advance through the module input voltage-output power transfer characteristic test, which is used to quantify the disturbance transfer gain of input voltage fluctuation on output power. This feedforward compensation correction amount is superimposed on the initial drive signal adjustment amount to offset the disturbance effect of input voltage fluctuation on the module output power. The initial drive signal adjustment amount and the feedforward compensation correction amount are algebraically added to obtain the drive signal adjustment amount after input voltage feedforward compensation. The complete expression of the drive signal adjustment after input voltage feedforward compensation is the algebraic sum of the proportional control component, the derivative control component, the integral control component, and the feedforward compensation correction. This algebraic sum includes both the feedback adjustment component based on the current power deviation and the deviation change trend, and the disturbance feedforward compensation component for input voltage fluctuations, thus realizing the synergistic effect of feedback control and feedforward control.

[0050] Based on the drive signal adjustment of each DC-DC power module, corresponding power adjustment commands are generated and sent to the drive control terminal of the corresponding DC-DC power module to adjust the duty cycle or switching frequency of the switching transistors of each DC-DC power module, forming a power closed-loop tracking control, so that the actual output power of each DC-DC power module follows the optimal target power value. For each DC-DC power module, the drive signal adjustment amount calculated in the second step is obtained, along with the current duty cycle and switching frequency of the switching transistor. Based on the drive signal adjustment amount, the required drive signal adjustment method is determined: a positive value indicates an increase in the duty cycle to boost output power, a negative value indicates a decrease in the duty cycle to reduce output power, and zero value indicates no adjustment is needed. The absolute value of the drive signal adjustment is converted into a corresponding duty cycle adjustment step size. The current switching transistor duty cycle is algebraically superimposed with the duty cycle adjustment step size to obtain the target switching transistor duty cycle. After determining the target duty cycle, it is encapsulated into a digital power adjustment command according to a preset encoding format. This command contains the module identification information of the corresponding DC-DC power module and the target switching transistor duty cycle value to be achieved. For each DC-DC power module, the generated power regulation command is sent to the drive control terminal of that module via a signal transmission line. Upon receiving the power regulation command, the drive control terminal of each DC-DC power module parses the target switching duty cycle value from the command and adjusts the ratio between the power switch's on-time and switching cycle according to this target value, causing the power switch to switch on and off according to the new duty cycle. After the drive signal adjustment is completed, the output power of each DC-DC power module changes accordingly. At this point, the current output voltage and current values ​​are re-acquired through the voltage and current sampling circuits at the output terminal, and the current actual output power value is calculated. The updated actual output power value is compared again with the optimal target power value to calculate the new power deviation and deviation change rate, and then the next round of drive signal adjustment calculation and power regulation command generation and transmission process begins. This process is periodically repeated during power system operation, forming a continuous loop control chain of deviation detection, adjustment calculation, drive signal adjustment, and deviation detection again. Under the continuous action of this cyclic control link, when the power deviation is reduced to within the preset allowable error range, the actual output power of each DC-DC power module is considered to have successfully followed the optimal target power value. The entire cyclic control process in which the actual output power of each DC-DC power module always maintains a dynamic following state around the optimal target power value is called power closed-loop tracking control.

[0051] In some embodiments, reference Figure 3The figure is a schematic diagram of a power system structure composed of multiple parallel DC-DC power modules in some embodiments of this application. The power system applies a DC-DC power module efficiency self-optimization method. By collecting the total power demand of the system and the operating parameters of each module, a module power-efficiency mapping relationship is constructed. Under the power allocation constraint, the optimal output power of each module is solved, and adjustment commands are issued to control the operation of each parallel DC-DC power module in the figure, thereby maximizing the overall operating efficiency of the system.

[0052] Furthermore, in another aspect of this application, in some embodiments, this application provides a DC-DC power module efficiency self-optimization system, referencing... Figure 4 The figure is a schematic diagram of the structure of a DC-DC power module efficiency self-optimization system according to some embodiments of this application. The DC-DC power module efficiency self-optimization system 400 includes: a data acquisition module 401, a processing module 402, and an execution module 403, which are described below: The acquisition module 401 in this application is mainly used to detect the real-time total power demand of the power system and the operating status parameters of each DC-DC power module in real time. Processing module 402, in this application, is used to determine the power allocation constraints under the current operating conditions of the power system based on the real-time total power demand and the power output capability of each DC-DC power module. It should be noted that the processing module 402 in this application is also used to establish a mapping relationship between the output power and operating efficiency of each DC-DC power module based on the efficiency characteristic data of each DC-DC power module in the full power operating range and each operating state parameter. Additionally, it should be noted that the processing module 402 in this application is also used to determine the optimal target power value of each DC-DC power module that maximizes the overall operating efficiency of the power system based on the mapping relationship and under the premise of satisfying the power allocation constraints, with the goal of maximizing the overall operating efficiency of the power system. The execution module 403 in this application is mainly used to send power adjustment commands to each DC-DC power module according to the optimal target power value, so as to control each DC-DC power module to output the corresponding power.

[0053] In addition, this application also provides a computer device, the computer device including a memory and a processor, the memory storing code, the processor being configured to acquire the code and execute the above-described DC-DC power module efficiency self-optimization method.

[0054] In some embodiments, reference Figure 5The figure is a schematic diagram of the structure of a computer device implementing a DC-DC power module efficiency self-optimization method according to some embodiments of this application. The DC-DC power module efficiency self-optimization method in the above embodiments can... Figure 5 The computer device shown is used to implement this, and the computer device 500 includes at least one processor 501, a communication bus 502, a memory 503, and at least one communication interface 504.

[0055] Processor 501 can be a general-purpose central processing unit (CPU) or an application-specific integrated circuit (ASIC).

[0056] The communication bus 502 can be used to transmit information between the aforementioned components.

[0057] Memory 503 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile optical discs, Blu-ray discs, etc.), magnetic disks or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. Memory 503 may exist independently and be connected to processor 501 via communication bus 502. Memory 503 may also be integrated with processor 501.

[0058] The memory 503 stores program code for executing the scheme of this application, and its execution is controlled by the processor 501. The processor 501 executes the program code stored in the memory 503. The program code may include one or more software modules. The method used in the above embodiments can be implemented by the processor 501 and one or more software modules in the program code in the memory 503.

[0059] Communication interface 504 uses any transceiver-like device to communicate with other devices or communication networks, such as Ethernet, radio access network (RAN), wireless local area networks (WLAN), etc.

[0060] In a specific implementation, as one example, a computer device may include multiple processors, each of which may be a single-core (single-CPU) processor or a multi-core (multi-CPU) processor. Here, a processor may refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0061] The aforementioned computer device can be a general-purpose computer device or a special-purpose computer device. In specific implementations, the computer device can be a desktop computer, a portable computer, a network server, a handheld digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. This application does not limit the type of computer device.

[0062] In addition, this application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for self-optimizing the efficiency of a DC-DC power module.

[0063] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0064] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for self-optimizing the efficiency of a DC-DC power module, applied to a power system comprising multiple DC-DC power modules connected in parallel, characterized in that, The method includes the following steps: Real-time detection of the total power demand of the power system and the operating status parameters of each DC-DC power module; Based on the real-time total power demand and the power output capability of each DC-DC power module, determine the power allocation constraints under the current operating conditions of the power system. Based on the efficiency characteristics data and operating status parameters of each DC-DC power module across the full power operating range, a mapping relationship between the output power and operating efficiency of each DC-DC power module is established. With the goal of maximizing the overall operating efficiency of the power system, and based on the mapping relationship, the optimal target power value of each DC-DC power module that maximizes the overall operating efficiency is determined under the premise of satisfying the power allocation constraints. According to the optimal target power value, a power adjustment command is sent to each DC-DC power module to control each DC-DC power module to output the corresponding power.

2. The method as described in claim 1, characterized in that, Specifically, it includes: The operating status parameters include the output voltage, output current, module temperature, and switching frequency of each DC-DC power module, as well as the input voltage and input current of each DC-DC power module.

3. The method as described in claim 1, characterized in that, Real-time detection of the total power demand of the power system and the operating status parameters of each DC-DC power module specifically includes: The total output voltage and total output current of the power system are collected in real time by voltage and current sensors installed at the total output terminal of the power system, and the real-time total power demand is determined based on the total output voltage and total output current. The operating status parameters of each DC-DC power module are obtained by collecting the output voltage and current, and input voltage and current of each DC-DC power module through voltage sampling circuits and current sampling circuits set at the output / input terminals of each DC-DC power module, respectively; collecting the module temperature through temperature sensors set inside each DC-DC power module; and obtaining the current switching frequency by reading the pulse width modulation drive signal of each DC-DC power module.

4. The method as described in claim 1, characterized in that, Based on the real-time total power demand and the power output capability of each DC-DC power module, the power allocation constraints under the current operating conditions of the power system specifically include: Obtain the power output capability of each DC-DC power module under the current operating status parameters; Based on the power output capability of each DC-DC power module, determine the available power range of each DC-DC power module; Based on the real-time total power demand, configure the sum of the allocated power of each DC-DC power module to equal the real-time total power demand; The power allocation constraint is defined as follows: the sum of the allocated power of each DC-DC power module equals the real-time total power demand, and the allocated power of each DC-DC power module is within the corresponding available power range.

5. The method as described in claim 1, characterized in that, Based on the efficiency characteristics and operating parameters of each DC-DC power module across its full power operating range, a mapping relationship between the output power and operating efficiency of each DC-DC power module is established, specifically including: Obtain efficiency characteristic data for each DC-DC power module under multiple preset power operating points, corresponding to different module temperatures and input voltage conditions; Using the output power and operating state parameters of each DC-DC power module as input variables, multidimensional surface fitting is performed on the efficiency characteristic data to obtain the dynamic efficiency characteristic curve between the output power and operating efficiency of each DC-DC power module in the full operating condition space. The mapping relationship between the output power and operating efficiency of each DC-DC power module is determined based on the dynamic efficiency characteristic curve.

6. The method as described in claim 1, characterized in that, With the goal of maximizing the overall operating efficiency of the power system, and based on the mapping relationship, the optimal target power values ​​for each DC-DC power module that maximize the overall operating efficiency are determined, under the premise of satisfying the power allocation constraints. Specifically, this includes: Based on the mapping relationship between the output power and operating efficiency of each DC-DC power module, the estimated input power values ​​under different power allocation combinations of each DC-DC power module are calculated respectively. The overall operating efficiency of the power system under each power allocation combination is determined based on the estimated values ​​of each input power. Using the power allocation of each DC-DC power module as the decision variable, the overall operating efficiency of the power system as the objective function, and the power allocation constraints as the constraints, a mathematical model for optimizing the efficiency of the power system is constructed. Within the feasible region of the efficiency optimization mathematical model, the decision variables are iteratively solved to obtain the optimal solution vector that makes the objective function reach its global maximum. The values ​​of each decision variable in the optimal solution vector are determined as the optimal target power values ​​of the corresponding DC-DC power modules.

7. The method as described in claim 1, characterized in that, Sending power adjustment commands to each DC-DC power module according to the optimal target power value to control each DC-DC power module to output the corresponding power specifically includes: Compare the optimal target power value of each DC-DC power module with the current actual output power of each DC-DC power module, and calculate the power deviation and deviation change rate of each DC-DC power module. Based on the power deviation and the rate of change of deviation, and combined with the current input voltage value of each DC-DC power module, calculate the required drive signal adjustment for each DC-DC power module. Based on the adjustment of the drive signal of each DC-DC power module, a corresponding power adjustment command is generated and sent to the drive control terminal of the corresponding DC-DC power module to adjust the duty cycle or switching frequency of the switching transistor of each DC-DC power module, forming a power closed-loop tracking control, so that the actual output power of each DC-DC power module follows the optimal target power value.

8. A DC-DC power module efficiency self-optimization system, which uses the method of any one of claims 1 to 7 to perform power module efficiency self-optimization, and is applied to a power system comprising multiple DC-DC power modules connected in parallel, characterized in that, The DC-DC power module efficiency self-optimization system includes: The acquisition module is used to detect the real-time total power demand of the power system and the operating status parameters of each DC-DC power module in real time. The processing module is used to determine the power allocation constraints of the power system under the current operating conditions based on the real-time total power demand and the power output capability of each DC-DC power module. The processing module is also used to establish a mapping relationship between the output power and operating efficiency of each DC-DC power module based on the efficiency characteristic data of each DC-DC power module in the full power operating range and various operating status parameters. The processing module is further configured to determine the optimal target power value of each DC-DC power module that maximizes the overall operating efficiency of the power system, based on the mapping relationship and under the premise of satisfying the power allocation constraints, with the goal of maximizing the overall operating efficiency of the power system. The execution module is used to send power adjustment commands to each DC-DC power module according to the optimal target power value, so as to control each DC-DC power module to output the corresponding power.

9. A computer device, characterized in that, The computer device includes a memory and a processor, the memory storing code, and the processor being configured to retrieve the code and execute the DC-DC power module efficiency self-optimization method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the DC-DC power module efficiency self-optimization method as described in any one of claims 1 to 7.

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