An extended phase-shift current optimization control method and device of a dual active bridge converter, a terminal device, and a storage medium

Abstract

This invention discloses an extended phase-shift current optimization control method, device, terminal equipment, and storage medium for a dual active bridge converter, belonging to the field of converter modulation technology. The method involves: acquiring the current power operation data of the dual active bridge converter; constructing an optimization model with the goal of minimizing the effective value of the inductor current, along with corresponding equality and inequality constraints; solving for the current optimal inner phase-shift duty cycle and the optimal outer phase-shift duty cycle; and finally optimizing the inductor current based on the optimal inner and outer phase-shift duty cycles. By implementing this invention, the problem of significantly increased switching losses and consequently low overall operating efficiency of the dual active bridge converter can be solved by using existing methods that simply minimize the root mean square of the inductor current as the optimization objective.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of converter modulation technology, and particularly relates to an extended phase-shift current optimization control method and device of a dual active bridge converter, a terminal device and a storage medium. BACKGROUND

[0002] With the development of digital technology, the power consumption of data centers continues to grow, and the requirements for power supply systems are increasing. Compared with the traditional alternating current architecture, direct current power distribution has become an important direction because it reduces the conversion link and reduces the loss. As a key equipment of the direct current system, the dual active bridge (DAB) converter in the power electronic transformer has the advantages of high-frequency isolation, bidirectional energy transmission, and easy parallel connection, and is widely used. The control of the dual active bridge converter is usually extended phase-shift (EPS) modulation. Therefore, improving the operating efficiency of the dual active bridge converter under EPS modulation is an important task at present.

[0003] In the prior art, the method of simply minimizing the root mean square of inductance current as the optimization target is usually used to reduce the conduction loss of power devices and the copper loss of high-frequency magnetic devices, but this method often ignores the constraint of soft switching of switching devices, resulting in that although the conduction loss is reduced, the switching devices cannot realize zero-voltage turn-on under some working conditions, which significantly increases the switching loss, and there is a problem of low overall operating efficiency of the dual active bridge converter. SUMMARY

[0004] The present application provides an extended phase-shift current optimization control method and device of a dual active bridge converter, a terminal device and a storage medium, which can solve the problem that the method of simply minimizing the root mean square of inductance current as the optimization target in the prior art reduces the conduction loss of power devices and the copper loss of high-frequency magnetic devices, which significantly increases the switching loss due to the inability of the switching devices to realize zero-voltage turn-on, and then there is a problem of low overall operating efficiency of the dual active bridge converter.

[0005] An embodiment of the present application provides an extended phase-shift current optimization control method of a dual active bridge converter, comprising: obtaining current power operating data of the dual active bridge converter; According to the above power operating data, an optimization model is constructed with the minimum effective value of inductance current as the target, and corresponding equality constraints and inequality constraints; wherein the equality constraints represent that the output power of the dual active bridge converter satisfies a preset active power reference value, and the inequality constraints are used to represent the constraint conditions required by the inductance current under the condition that all power devices realize zero-voltage turn-on; According to the above power operating data, the optimization model is solved under the equality constraints and inequality constraints to obtain the current optimal inner phase-shift duty cycle and the optimal outer phase-shift duty cycle; Based on the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle, the bridge arm switches in the above dual active bridge converter are driven to turn on and off in order to optimize the inductor current.

[0006] Furthermore, the objective function of the above optimization model is: In the formula, Indicates the effective value of the inductor current. Indicates the duty cycle of the inner phase shift. Indicates the duty cycle of the outgoing phase. The switching period is represented by t, where t represents time. Describe the objective function. This represents the piecewise function of inductor current.

[0007] Furthermore, the above equation constraints are: In the formula, P represents the output power of the dual active bridge converter. Indicates half a switching cycle. This indicates the AC port voltage of the primary-side full-bridge inverter. Indicates inductor current. Indicates the turns ratio of the primary and secondary sides of the transformer. This indicates the preset active power reference value.

[0008] Furthermore, the above inequality constraints are: In the formula, Indicates the start time of the half-cycle The inductor current at that time Indicates the voltage switching time corresponding to the inward shift. The inductor current at that time Indicates the voltage switching time corresponding to the outward shift. The inductor current at that time Indicates the end time of the half-cycle The inductor current at that time.

[0009] Furthermore, based on the aforementioned power operation data, and under the aforementioned equality and inequality constraints, the aforementioned optimization model is solved to obtain the current optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle, including: An initial population is generated based on the preset inner phase duty cycle threshold range and the preset outer phase duty cycle threshold range; wherein, the population includes several individuals, each individual representing a parameter combination consisting of an inner phase duty cycle and an outer phase duty cycle; Based on the above power operation data, initial population, and the above equality and inequality constraints, the above optimization model is repeatedly solved to obtain the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle. The above-mentioned solution operations include: Obtain the current population and the historical global best fitness; where the initial population is the same as the initial population mentioned above, and the initial global best fitness is infinity; Based on the individual, the above equality constraints, inequality constraints, and the above power operation data, the current individual fitness of each individual in the current population is calculated; The minimum fitness among all current individual fitness values ​​is taken as the optimal fitness of the current population. Determine if the current number of iterations is not less than the preset maximum number of iterations; If the current number of iterations is not less than the preset maximum number of iterations, then the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle are determined based on the relationship between the current optimal fitness of the population and the historical global optimal fitness. Otherwise, if the current number of iterations is less than the preset maximum number of iterations, the individuals in the current population are updated. At the same time, if the current population's optimal fitness is less than the historical global optimal fitness, the historical global optimal fitness is updated based on the current population's optimal fitness.

[0010] Furthermore, based on the relationship between the current optimal fitness of the population and the historical global optimal fitness, the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle are determined, including: Determine whether the current optimal fitness of the population is less than the historical global optimal fitness; If the current optimal fitness of the population is less than the historical global optimal fitness, the inner phase shift duty cycle and the outer phase shift duty cycle of the individual corresponding to the current optimal fitness of the population are taken as the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle, respectively. Otherwise, the inner phase duty cycle and outer phase duty cycle of the individual corresponding to the historical global optimal fitness are taken as the optimal inner phase duty cycle and the optimal outer phase duty cycle, respectively.

[0011] Based on the above method embodiments, the present invention provides corresponding apparatus embodiments; This invention provides an extended phase-shift current optimization control device for a dual active bridge converter, comprising: The system includes a power operation data acquisition module, a model building module, a duty cycle calculation module, and an inductor current optimization module. The aforementioned power operation data acquisition module is used to acquire the current power operation data of the dual active bridge converter; The aforementioned model building module is used to construct an optimization model based on the aforementioned power operation data, with the goal of minimizing the effective value of the inductor current, as well as the corresponding equality constraints and inequality constraints. The aforementioned equality constraints indicate that the output power of the aforementioned dual active bridge converter meets the preset active power reference value, and the aforementioned inequality constraints are used to indicate the constraint conditions that the inductor current needs to meet when all power devices achieve zero-voltage turn-on. The duty cycle calculation module is used to solve the optimization model based on the power operation data and under the equality and inequality constraints to obtain the current optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle. The aforementioned inductor current optimization module is used to drive the bridge arm switches in the aforementioned dual active bridge converter to turn on and off according to the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle, so as to optimize the inductor current.

[0012] Furthermore, the objective function of the above optimization model is constructed as follows: In the formula, Indicates the effective value of the inductor current. Indicates the duty cycle of the inner phase shift. Indicates the duty cycle of the outgoing phase. The switching period is represented by t, where t represents time. Describe the objective function. This represents the piecewise function of inductor current.

[0013] Based on the above method embodiments, the present invention provides a corresponding terminal device embodiment; The present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the extended phase-shift current optimization control method of a dual active bridge converter described in any embodiment of the present invention.

[0014] Based on the above method embodiments, the present invention provides a corresponding storage medium embodiment; The present invention provides a storage medium including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the extended phase-shift current optimization control method for a dual active bridge converter described in any embodiment of the present invention.

[0015] The embodiments of the present invention have the following beneficial effects: This invention provides an extended phase-shift current optimization control method, apparatus, terminal device, and storage medium for a dual active bridge converter. The method includes: acquiring the current power operation data of the dual active bridge converter; subsequently, based on the power operation data, constructing an optimization model with the objective of minimizing the effective value of the inductor current, along with corresponding equality constraints and inequality constraints; wherein the equality constraints indicate that the output power of the dual active bridge converter meets a preset active power reference value, and the inequality constraints represent the constraints that the inductor current must satisfy when all power devices achieve zero-voltage turn-on; further, based on the power operation data, solving the optimization model under the equality and inequality constraints to obtain the current optimal inner phase-shift duty cycle and the optimal outer phase-shift duty cycle; finally, based on the optimal inner phase-shift duty cycle and the optimal outer phase-shift duty cycle, driving the bridge arm switches in the dual active bridge converter to switch on and off to optimize the inductor current. Therefore, in this invention, under the constraints of the equation indicating that the output power of the aforementioned dual active bridge converter satisfies the preset active power reference value, and the constraints that the inductor current must satisfy when all power devices achieve zero-voltage turn-on, the optimization model aimed at minimizing the effective value of the inductor current is solved. This yields the optimal inner phase-shift duty cycle and the optimal outer phase-shift duty cycle that ensure all power devices achieve zero-voltage turn-on at the turn-on time of each switch. Therefore, when the converter is modulated using these two optimal duty cycles, the conduction losses of the power devices and the copper losses of the high-frequency magnetic devices are reduced, while switching losses are also reduced, thereby significantly improving the overall operating efficiency of the converter. Attached Figure Description

[0016] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0017] Figure 1 This is a flowchart illustrating an extended phase-shift current optimization control method for a dual active bridge converter according to an embodiment of the present invention.

[0018] Figure 2 This is a topology diagram of a dual active bridge converter provided in an embodiment of the present invention.

[0019] Figure 3 This is a control schematic diagram of a DC flexible device for a dual active bridge converter provided in an embodiment of the present invention.

[0020] Figure 4 This is a graph showing the comparison results of the effective values ​​of inductor current provided in an embodiment of the present invention.

[0021] Figure 5 This is a schematic diagram of the structure of an extended phase-shift current optimization control device for a dual active bridge converter provided in an embodiment of the present invention. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0024] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0025] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0026] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0027] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0028] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0029] See Figure 1 To address the problem that existing methods that solely minimize the root mean square of inductor current to reduce power device conduction losses and high-frequency magnetic device copper losses can lead to significantly increased switching losses due to the inability of switching devices to achieve zero-voltage turn-on, resulting in low overall operating efficiency of dual active bridge converters, this invention provides an extended phase-shift current optimization control method for dual active bridge converters, comprising: Step S101: Obtain the current power operation data of the dual active bridge converter; Specifically, the dual active bridge converter is a key component in data center DC power supply systems and a crucial factor determining overall efficiency. Due to its advantages such as high-frequency isolation, bidirectional power transmission, and ease of modular parallel connection, the dual active bridge converter is widely used in the isolation stage of power electronic transformers. A schematic diagram of the dual active bridge converter topology is shown below. Figure 2 As shown, Figure 2 "in "", "", "", "", "", "", "as well as" "" indicates 8 power switching transistors, and "A", "B", "C" and "D" are circuit nodes. Among them, "A" and "B" together form the primary side high-frequency AC input port, and "C" and "D" together form the secondary side high-frequency AC output port. "" indicates the equivalent transmission inductance, and "n:1" indicates the turns ratio of the primary and secondary sides of the high-frequency transformer.

[0030] Specifically, the aforementioned power operation data includes: input DC voltage, output DC voltage, turns ratio of the primary and secondary sides of the high-frequency transformer, AC port voltage of the primary full-bridge inverter, switching cycle, and half-switching cycle.

[0031] Step S102: Based on the above power operation data, construct an optimization model with the goal of minimizing the effective value of the inductor current, as well as the corresponding equality constraints and inequality constraints; wherein, the above equality constraints indicate that the output power of the above dual active bridge converter meets the preset active power reference value, and the above inequality constraints are used to indicate the constraint conditions that the inductor current needs to meet when all power devices achieve zero voltage turn-on. Specifically, based on the direction of the inductor current at different critical time points, the converter's operating modes within half a switching cycle can be divided as shown in the table below: As shown in the table above, The inductor current is represented by the inductor voltage. Under extended phase-shift modulation, the inductor voltage of the dual active bridge converter exhibits a piecewise constant value within each switching cycle. Therefore, the inductor current also changes linearly in a piecewise manner. The inductor current within half a switching cycle can be divided into several linear segments, with the corresponding key time points being: Half-cycle starting point; The voltage switching time corresponding to the inward shift; The voltage switching time corresponding to the outward shift; Half-cycle end point; Due to the inductor current under steady-state conditions It satisfies periodic continuity within the switching cycle, that is... Therefore, only half a switching cycle needs to be analyzed. With fixed input DC voltage, output DC voltage, turns ratio of the high-frequency transformer primary and secondary sides, and equivalent transmission inductance of the dual active bridge, and given the inner and outer phase-shifting duty cycles, the trend of inductor current variation in each segment is determined by the sign of the inductor voltage. The essential difference between different operating modes lies in: , and The sign relationships at the three points are different. Therefore, based on the positive and negative relationships of the current at the three key moments mentioned above, when the duty cycle of the outer phase shift is greater than that of the inner phase shift, the piecewise expression for the inductor current can be expressed as: In the formula, This represents the inductor current at the start of a half-cycle when the duty cycle of the outer phase shift is greater than that of the inner phase shift. N represents the turns ratio of the transformer's primary and secondary sides, and k represents the voltage matching ratio. Indicates the input DC voltage. Indicates the output DC voltage. Indicates the duty cycle of the inner phase shift. This indicates the duty cycle of the outgoing phase.

[0032] For another case where the duty cycle of the outer phase shift is less than that of the inner phase shift, the same principle can be used to obtain the piecewise expression for current and inductance as shown below: In the formula, This represents the inductor current when the duty cycle of the outer phase shift is less than that of the inner phase shift.

[0033] Specifically, after obtaining the piecewise expression for the inductor current, the effective value of the inductor current can be calculated by integrating the piecewise expression over one switching cycle. Then, an optimization model is constructed with the goal of minimizing the effective value of the inductor current. At the same time, corresponding equality constraints and inequality constraints are constructed by combining power operation data.

[0034] It should be noted that, regardless of whether the inner phase shift duty cycle is greater than the outer phase shift duty cycle or less than the outer phase shift duty cycle, the segmented expression of the inductor current may not be exactly the same, but it can be obtained through a unified segmented modeling method. The only difference is the change in the voltage segmentation order and the current sign at critical moments, which does not affect the subsequent optimization model construction and solution process.

[0035] Preferably, by dividing the working mode, it is possible to determine whether the inductor current crosses zero within half a cycle, whether the switching device meets the zero voltage turn-on (ZVS) condition at each turn-on instant, whether the RMS current (i.e., the root mean square of the inductor current) integration interval contains a sign change point, and to determine the location where the current peak or effective value appears.

[0036] In a preferred embodiment, the objective function of the above optimization model is: In the formula, Indicates the effective value of the inductor current. Indicates the duty cycle of the inner phase shift. Indicates the duty cycle of the outgoing phase. The switching period is represented by t, where t represents time. Describe the objective function. This represents the piecewise function of inductor current.

[0037] Specifically, by integrating the piecewise expression of the inductor current over one switching cycle, the expression for the effective value of the inductor current in the objective function is obtained. Then, by minimizing the effective value of the inductor current, the objective function can be obtained. The decision variables in the objective function are the inner phase shift duty cycle and the outer phase shift duty cycle.

[0038] It should be noted that in the objective function This can represent the effective value of the inductor current when the inner phase shift duty cycle is greater than the outer phase shift duty cycle, or it can represent the effective value of the inductor current when the inner phase shift duty cycle is less than the outer phase shift duty cycle. The only difference is that the piecewise expressions for the inductor current are different in the two cases. In this case, it is only necessary to construct the solution optimization model based on the corresponding piecewise expressions for the inductor current.

[0039] In this preferred embodiment, the objective function of the optimization model is constructed by calculating the root mean square of the inductor current and minimizing the root mean square of the inductor current.

[0040] In another preferred embodiment, the above equality constraint is: In the formula, P represents the output power of the dual active bridge converter. Indicates half a switching cycle. This indicates the AC port voltage of the primary-side full-bridge inverter. Indicates inductor current. Indicates the turns ratio of the primary and secondary sides of the transformer. This indicates the preset active power reference value.

[0041] Specifically, the above equation constraints can be used to constrain the combination of the inner and outer phase shift duty cycles through the power transfer model, so that the converter's output power meets the preset per-unit power requirement.

[0042] In this preferred embodiment, the converter's output power is made to meet a preset per-unit power requirement. This establishes an equality constraint.

[0043] In another preferred embodiment, the above inequality constraint is: In the formula, Indicates the start time of the half-cycle The inductor current at that time Indicates the voltage switching time corresponding to the inward shift. The inductor current at that time Indicates the voltage switching time corresponding to the outward shift. The inductor current at that time Indicates the end time of the half-cycle The inductor current at that time.

[0044] Specifically, the aforementioned inequality constraint is also a zero-voltage turn-on constraint for all power devices. This constraint requires that at the turn-on time of each switch, the direction of the inductor current satisfies the conduction condition of the reverse parallel diode, so as to ensure that all power devices achieve zero-voltage turn-on.

[0045] In this preferred embodiment, the above-mentioned inequality constraint is constructed by constraining the direction of the inductor current at the turn-on time of each switch, while ensuring that the power device achieves zero-voltage turn-on.

[0046] Step S103: Based on the above power operation data, solve the above optimization model under the above equality constraints and inequality constraints to obtain the current optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle. Specifically, this invention employs the whale optimization algorithm to solve the optimization model, obtaining the optimal inner phase duty cycle and the optimal outer phase duty cycle. In the whale optimization algorithm, the whale population positions are initialized within the feasible solution space. The inner and outer phase duty cycles are used as position parameters for individual whales. By simulating whales' encirclement predation, bubble net attacks, and random search behaviors, the combination of position parameters is continuously updated in a multi-dimensional parameter space until the maximum number of iterations is met, outputting the final optimal result.

[0047] Preferably, the present invention takes minimizing the root mean square value of the inductor current as the optimization objective. By systematically optimizing the extended phase-shift modulation parameters, the conduction loss of power switching devices and the copper loss of high-frequency transformers can be effectively reduced, thereby improving the operating efficiency of the dual active bridge converter from the source. It is particularly suitable for data center power supply scenarios with high energy efficiency requirements.

[0048] Preferably, the present invention introduces a zero-voltage turn-on constraint for full-power devices (i.e., the above-mentioned inequality constraint) during the optimization process, which avoids the problem of existing optimizations that only focus on RMS current and ignore soft-switching conditions, and achieves synergistic optimization of low current RMS value and full device soft-switching characteristics.

[0049] Preferably, the present invention uses the whale optimization algorithm to search for the phase shift parameters, which has strong global optimization ability and the ability to handle complex nonlinear constraints. It can stably converge to the optimal solution that meets the requirements of power balance and soft switching under multiple operating modes, and is suitable for engineering applications under complex operating conditions.

[0050] In a preferred embodiment, the optimization model is solved based on the power operation data, under the aforementioned equality and inequality constraints, to obtain the current optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle, including: An initial population is generated based on the preset inner phase duty cycle threshold range and the preset outer phase duty cycle threshold range; wherein, the population includes several individuals, each individual representing a parameter combination consisting of an inner phase duty cycle and an outer phase duty cycle; Based on the above power operation data, initial population, and the above equality and inequality constraints, the above optimization model is repeatedly solved to obtain the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle. The above-mentioned solution operations include: Obtain the current population and the historical global best fitness; where the initial population is the same as the initial population mentioned above, and the initial global best fitness is infinity; Specifically, the aforementioned historical global optimal fitness refers to the best global optimal fitness obtained during the historical iterative solution process.

[0051] Based on the individual, the above equality constraints, inequality constraints, and the above power operation data, the current individual fitness of each individual in the current population is calculated; Specifically, individual fitness is calculated using the following formula: In the formula, Indicates individual fitness. Represents the objective function value. This represents the weight corresponding to the equality constraint penalty term. This represents the penalty term for equality constraints. This represents the analytical model of the transmission power of a dual active bridge under extended phase-shift modulation. This represents the weight corresponding to the inequality constraint penalty term. This represents the penalty term for inequality constraints, and m represents the number of ZVS constraint functions. Let j represent the j-th ZVS constraint function.

[0052] It should be noted that the above individual fitness formula, in order to achieve inductor current optimization while satisfying equality and inequality constraints, constructs an individual fitness function that includes constraint penalty terms. In the entire individual fitness function, the objective function represents the effective value of the inductor current, thereby reducing conduction losses and copper losses in magnetic devices. When the phase shift parameter combination corresponding to an individual cannot satisfy power balance, its fitness value is increased through equality constraint penalty terms, causing it to be gradually eliminated during the optimization process. Simultaneously, when the inductor current direction does not satisfy inequality constraints, the corresponding constraint function... The value is less than 0, thus generating a penalty value. The two weights in the formula can be dynamically adjusted with the number of iterations t to enhance the optimization process's ability to suppress infeasible solutions and guide the whale population to gradually converge towards the region that satisfies the power balance and soft-switching conditions of all devices.

[0053] The minimum fitness among all current individual fitness values ​​is taken as the optimal fitness of the current population. Determine if the current number of iterations is not less than the preset maximum number of iterations; If the current number of iterations is not less than the preset maximum number of iterations, then the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle are determined based on the relationship between the current optimal fitness of the population and the historical global optimal fitness. Otherwise, if the current number of iterations is less than the preset maximum number of iterations, the individuals in the current population are updated. At the same time, if the current population's optimal fitness is less than the historical global optimal fitness, the historical global optimal fitness is updated based on the current population's optimal fitness.

[0054] Specifically, if the current number of iterations is less than the preset maximum number of iterations, it indicates that further iterations are needed. Therefore, the current individual needs to be updated. When updating, it is necessary to ensure that the updated individual is within the feasible region limited by the preset inner phase shift duty cycle threshold range and the preset outer phase shift duty cycle threshold range. Secondly, for individuals that do not meet the inequality constraints, a penalty function can be introduced to gradually guide the population to converge toward the target (i.e., low RMS current) region that meets the inequality constraints.

[0055] Therefore, in this invention, the position vector of each body (i.e., the numerical combination of the inner phase duty cycle and the outer phase duty cycle corresponding to each body) is defined as: In the formula, Let represent the position of the i-th individual at time t. This represents the duty cycle of the inner phase shift in the i-th individual at time t. Let represent the duty cycle of the outward shift phase in the i-th individual at time t.

[0056] Subsequently, when updating an individual, a random number p in the interval [0,1] is first generated, and then the current coefficient A is calculated: In the formula, This represents the convergence factor, whose value decreases linearly from 2 to 0 with each repeated solution iteration. This represents a random vector with the interval [0,1].

[0057] Then, based on the absolute value of the current coefficient A and the size of the random number p, the individual is updated: When |A| < 1 and p < 0.5, the prey encirclement mechanism in the whale optimization algorithm is used for individual updates: In the formula, Let C represent the distance between the i-th individual and the globally optimal individual at time t under the prey-surrounding mechanism, and let C represent another coefficient. Let [the vector] represent another random vector within the interval [0,1]. Let represent the position of the individual corresponding to the optimal fitness of the population at time t. This represents the position of the i-th individual at time t. This represents the updated position of the i-th individual.

[0058] When |A|≥1 and p<0.5, a random search mechanism is used for updating: In the formula, This represents the distance between the i-th individual and the randomly selected individual at time t under the random search mechanism. This represents the position of a randomly selected individual in the current population.

[0059] When p≥0.5, a spiral bubble network attack mechanism is used for individual updates: In the formula, Let represent the distance between the i-th individual and the global optimal individual at time t under the spiral bubble net attack mechanism, b represent the spiral shape constant, and l' represent a random number in the interval [-1, 1].

[0060] It should be noted that, because the individual fitness function was constructed with a constraint penalty term, if an individual does not satisfy the inequality constraint during updates, its fitness will increase according to the fitness function, putting it at a disadvantage in the "optimal individual selection." Thus, subsequent updates to the whale swarm will naturally converge towards the region with low RMS current and satisfying the soft-switching condition. For individuals that do not violate the inequality constraint, i.e., satisfy: At this time there is =0, meaning that no additional inequality constraint penalty is imposed on this individual, and its fitness function degenerates to: If it also satisfies the equality constraint, then we further have: At this point, the individual iterates its position according to the update mechanism of the standard whale optimization algorithm. The update method still adopts the above-mentioned prey encirclement mechanism, spiral bubble net attack mechanism or random search mechanism. There is no need to modify the position formula. It only obtains a higher retention probability and guidance role in the population competition by having a smaller fitness value.

[0061] In summary, for individuals that satisfy the constraints: update according to the standard whale optimization update formula without penalty; for individuals that do not satisfy the constraints: update according to the whale optimization formula as well, but add a corresponding penalty term to their fitness to make them less likely to become the current best individual, thus gradually guiding them out of the infeasible region.

[0062] In this preferred embodiment, the optimization model was solved using the whale optimization algorithm to obtain the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle.

[0063] In another preferred embodiment, the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle are determined based on the relationship between the current optimal fitness of the population and the historical global optimal fitness, including: Determine whether the current optimal fitness of the population is less than the historical global optimal fitness; If the current optimal fitness of the population is less than the historical global optimal fitness, the inner phase shift duty cycle and the outer phase shift duty cycle of the individual corresponding to the current optimal fitness of the population are taken as the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle, respectively. Otherwise, the inner phase duty cycle and outer phase duty cycle of the individual corresponding to the historical global optimal fitness are taken as the optimal inner phase duty cycle and the optimal outer phase duty cycle, respectively.

[0064] Specifically, if the current optimal fitness of the population is less than the historical global optimal fitness, it means that the individual corresponding to the current optimal fitness is the optimal individual obtained by the model. Therefore, the inner phase shift duty cycle and outer phase shift duty cycle of this optimal individual are taken as the final solution result. Otherwise, it means that the individual corresponding to the historical global optimal fitness is the optimal individual obtained by the model. Therefore, the inner phase shift duty cycle and outer phase shift duty cycle of the individual corresponding to the historical global optimal fitness are taken as the final solution result.

[0065] In this preferred embodiment, the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle are finally determined based on the relationship between the current optimal fitness of the population and the historical global optimal fitness.

[0066] Step S104: Based on the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle, drive the bridge arm switches in the above dual active bridge converter to turn on and off, so as to optimize the inductor current.

[0067] Specifically, the optimal inner and outer phase-shift duty cycles serve as control input parameters for the extended phase-shift modulator in the dual active bridge converter, generating PWM drive signals for each bridge arm switching device. More specifically, the optimal inner phase-shift duty cycle controls the phase difference between the input-side full bridge and the bridge arm switches, while the optimal outer phase-shift duty cycle controls the phase difference between the input-side and output-side full bridges. This phase control is implemented through a digital controller (e.g., DSP, FPGA, or MCU) and output to the power drive circuit, thereby controlling the on / off state of the power switches.

[0068] After controlling the turn-on and turn-off of the power switching transistors, the inductor current waveform of the dual active bridge converter can be further controlled based on the actual turn-on time of the power semiconductor devices, ultimately reducing device conduction losses, transformer copper losses, and switching losses.

[0069] Preferably, the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle can also reduce the effective value of the inductor current IRMS, while ensuring that each power device meets the zero voltage turn-on (ZVS) condition.

[0070] An illustrative control diagram of a DC flexible device with a dual active bridge converter is shown below. Figure 3 As shown, from Figure 3 As can be seen from this, firstly, based on the preset target voltage reference... The difference between the input DC voltage and the output DC voltage generates a voltage error signal. On one hand, the voltage error signal performs proportional-integral calculations through a PI controller, outputting an external phase-shift duty cycle. On the other hand, the voltage error signal, combined with the input DC voltage, calculates the voltage conversion ratio. Subsequently, based on the voltage conversion ratio and analog control commands, the internal phase-shift duty cycle is determined by looking up a table. This table pre-stores the optimal internal and external phase-shift duty cycles obtained after optimization using the whale optimization algorithm presented in this invention. Then, a specific modulation scheme is generated based on the internal and external phase-shift duty cycles to modulate the DAB converter.

[0071] Schematic, the extended phase-shift current optimization control method shown in this invention is compared with three existing extended phase-shift modulation strategies. The comparison results of the effective values ​​of the inductor current are shown in the figure below. Figure 4 As shown. Figure 4The "proposed multi-objective method" refers to the effective value of the inductor current obtained after using the extended phase-shift current optimization control method shown in this invention. "TPS mode 1" corresponds to the existing technology (reference: Q. Gu, L. Yuan, J. Nie, J. Sun, Z. Zhao et al. Current Stress Minimization of Dual-Active-Bridge DC–DC ConverterWithin the Whole Operating Range, IEEE Journal of Emerging and Selected Topics in Power Electronics, 2019, 7(1):129–142.), which uses three independent phase shift variables to reduce current stress. The optimal phase shift combination is derived through analytical modeling, thereby realizing the effective value of the inductor current under the modulation strategy of optimizing the peak or effective value of the current throughout the entire operating range. "TPS Mode 2" corresponds to the existing technology (reference: F. Lin, X. Zhang, X. Li, C. Sun, W. Cai, Z. Zhang et al. Automatic Triple Phase-Shift Modulation for DAB Converter With Minimized Power Loss, IEEE Transactions on Industry Applications, 2022, 58(3):3840–3851.), which automatically selects the phase shift combination, optimizes for minimum power loss, takes into account soft switching and efficiency optimization, and automatically adjusts the modulation parameters under different operating conditions to obtain the effective value of the inductor current.“EPS Mode 1” corresponds to the existing technology (in the literature: X. Li, X. Zhang, F. Lin, C. Sun, K. Mao et al. Artificial-Intelligence-Based Hybrid Extended PhaseShift Modulation for the Dual Active Bridge Converter With Full ZVS Range and Optimal Efficiency, IEEE Journal of Emerging and Selected Topics in PowerElectronics, 2023, 11(6):5569–5581.), which uses an artificial intelligence optimization strategy to achieve hybrid extended phase shift modulation and optimizes efficiency while ensuring the full ZVS range, resulting in the effective value of the inductor current. Figure 4 The horizontal axis, "Transmission Power," represents the different transmission power provided by the four methods, in units of pu, to obtain the effective value of the inductor current under different transmission power for each of the four methods. The vertical axis, "Root Mean Square Current," represents the obtained effective value of the inductor current, in units of A.

[0072] Indicative, from Figure 4 As can be seen, under the same operating conditions, the effective value of the inductor current obtained by implementing the extended phase-shift current optimization control method of the present invention is significantly lower than that of the other three prior art methods. Therefore, the present invention has significant advantages in reducing switching losses and copper losses.

[0073] Based on the above method embodiments, the present invention provides corresponding apparatus embodiments.

[0074] like Figure 5 As shown, an embodiment of the present invention provides an extended phase-shift current optimization control device for a dual active bridge converter, comprising: The system includes a power operation data acquisition module, a model building module, a duty cycle calculation module, and an inductor current optimization module. The aforementioned power operation data acquisition module is used to acquire the current power operation data of the dual active bridge converter; Specifically, dual active bridge converters are key equipment in DC power supply systems for data centers and are an important component that determines overall efficiency. Due to their advantages such as high-frequency isolation, bidirectional power transmission, and ease of modular parallel connection, dual active bridge converters are widely used in the isolation stage of power electronic transformers.

[0075] Specifically, the aforementioned power operation data includes: input DC voltage, output DC voltage, turns ratio of the primary and secondary sides of the high-frequency transformer, AC port voltage of the primary full-bridge inverter, switching cycle, and half-switching cycle.

[0076] The aforementioned model building module is used to construct an optimization model based on the aforementioned power operation data, with the goal of minimizing the effective value of the inductor current, as well as the corresponding equality constraints and inequality constraints. The aforementioned equality constraints indicate that the output power of the aforementioned dual active bridge converter meets the preset active power reference value, and the aforementioned inequality constraints are used to indicate the constraint conditions that the inductor current needs to meet when all power devices achieve zero-voltage turn-on. Specifically, after obtaining the piecewise expression for the inductor current, the effective value of the inductor current can be calculated by integrating the piecewise expression over one switching cycle. Then, an optimization model is constructed with the goal of minimizing the effective value of the inductor current. At the same time, corresponding equality constraints and inequality constraints are constructed by combining power operation data.

[0077] It should be noted that, regardless of whether the inner phase shift duty cycle is greater than the outer phase shift duty cycle or less than the outer phase shift duty cycle, the segmented expression of the inductor current may not be exactly the same, but it can be obtained through a unified segmented modeling method. The only difference is the change in the voltage segmentation order and the current sign at critical moments, which does not affect the subsequent optimization model construction and solution process.

[0078] Preferably, by dividing the working mode, it is possible to determine whether the inductor current crosses zero within half a cycle, whether the switching device meets the zero voltage turn-on (ZVS) condition at each turn-on instant, whether the RMS current (i.e., the root mean square of the inductor current) integration interval contains a sign change point, and to determine the location where the current peak or effective value appears.

[0079] The duty cycle calculation module is used to solve the optimization model based on the power operation data and under the equality and inequality constraints to obtain the current optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle. Specifically, this invention employs the whale optimization algorithm to solve the optimization model, obtaining the optimal inner phase duty cycle and the optimal outer phase duty cycle. In the whale optimization algorithm, the whale population positions are initialized within the feasible solution space. The inner and outer phase duty cycles are used as position parameters for individual whales. By simulating whales' encirclement predation, bubble net attacks, and random search behaviors, the combination of position parameters is continuously updated in a multi-dimensional parameter space until the maximum number of iterations is met, outputting the final optimal result.

[0080] Preferably, the duty cycle calculation module takes minimizing the root mean square value of the inductor current as the optimization objective. By optimizing the extended phase-shift modulation parameters, it can effectively reduce the conduction loss of power switching devices and the copper loss of high-frequency transformers, thereby improving the operating efficiency of the dual active bridge converter from the source. It is particularly suitable for data center power supply scenarios with high energy efficiency requirements.

[0081] Preferably, the duty cycle solving module introduces a zero-voltage turn-on constraint for full-power devices (i.e., the aforementioned inequality constraint) during the optimization process, which avoids the problem of existing optimizations that only focus on RMS current and ignore soft-switching conditions, and achieves coordinated optimization of low current RMS value and full device soft-switching characteristics.

[0082] Preferably, the duty cycle solving module uses the whale optimization algorithm to search for the phase shift parameters. It has strong global optimization capabilities and the ability to handle complex nonlinear constraints. It can stably converge to the optimal solution that meets the requirements of power balance and soft switching under multiple operating modes, making it suitable for engineering applications under complex operating conditions.

[0083] The aforementioned inductor current optimization module is used to drive the bridge arm switches in the aforementioned dual active bridge converter to turn on and off according to the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle, so as to optimize the inductor current.

[0084] Specifically, the optimal inner and outer phase-shift duty cycles serve as control input parameters for the extended phase-shift modulator in the dual active bridge converter, generating PWM drive signals for each bridge arm switching device. More specifically, the optimal inner phase-shift duty cycle controls the phase difference between the input-side full bridge and the bridge arm switches, while the optimal outer phase-shift duty cycle controls the phase difference between the input-side and output-side full bridges. This phase control is implemented through a digital controller (e.g., DSP, FPGA, or MCU) and output to the power drive circuit, thereby controlling the on / off state of the power switches.

[0085] After controlling the turn-on and turn-off of the power switching transistors, the inductor current waveform of the dual active bridge converter can be further controlled based on the actual turn-on time of the power semiconductor devices, ultimately reducing device conduction losses, transformer copper losses, and switching losses.

[0086] Preferably, the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle can also reduce the effective value of the inductor current IRMS, while ensuring that each power device meets the zero voltage turn-on (ZVS) condition.

[0087] In a preferred embodiment, the objective function of the above optimization model is constructed as follows: In the formula, Indicates the effective value of the inductor current. Indicates the duty cycle of the inner phase shift. Indicates the duty cycle of the outgoing phase. The switching period is represented by t, where t represents time. Describe the objective function. This represents the piecewise function of inductor current.

[0088] Specifically, by integrating the piecewise expression of the inductor current over one switching cycle, the expression for the effective value of the inductor current in the objective function is obtained. Then, by minimizing the effective value of the inductor current, the objective function can be obtained. The decision variables in the objective function are the inner phase shift duty cycle and the outer phase shift duty cycle.

[0089] It should be noted that in the objective function This can represent the effective value of the inductor current when the inner phase shift duty cycle is greater than the outer phase shift duty cycle, or it can represent the effective value of the inductor current when the inner phase shift duty cycle is less than the outer phase shift duty cycle. The only difference is that the piecewise expressions for the inductor current are different in the two cases. In this case, it is only necessary to construct the solution optimization model based on the corresponding piecewise expressions for the inductor current.

[0090] In another preferred embodiment, the above equality constraint is constructed as follows: In the formula, P represents the output power of the dual active bridge converter. Indicates half a switching cycle. This indicates the AC port voltage of the primary-side full-bridge inverter. Indicates inductor current. Indicates the turns ratio of the primary and secondary sides of the transformer. This indicates the preset active power reference value.

[0091] Specifically, the above equation constraints can be used to constrain the combination of the inner and outer phase shift duty cycles through the power transfer model, so that the converter's output power meets the preset per-unit power requirement.

[0092] In another preferred embodiment, the above inequality constraints are constructed as follows: In the formula, Indicates the start time of the half-cycle The inductor current at that time Indicates the voltage switching time corresponding to the inward shift. The inductor current at that time Indicates the voltage switching time corresponding to the outward shift. The inductor current at that time Indicates the end time of the half-cycle The inductor current at that time.

[0093] Specifically, the aforementioned inequality constraint is also a zero-voltage turn-on constraint for all power devices. This constraint requires that at the turn-on time of each switch, the direction of the inductor current satisfies the conduction condition of the reverse parallel diode, so as to ensure that all power devices achieve zero-voltage turn-on.

[0094] In another preferred embodiment, the duty cycle calculation module includes: Initial population generation unit and model solution unit; The aforementioned initial population generation unit is used to generate an initial population based on a preset inner phase duty cycle threshold range and a preset outer phase duty cycle threshold range; wherein, the population includes several individuals, and each individual represents a parameter combination consisting of an inner phase duty cycle and an outer phase duty cycle; The aforementioned model solving unit is used to repeatedly perform the solving operation on the aforementioned optimization model based on the aforementioned power operation data, initial population, and the aforementioned equality constraints and inequality constraints, so as to obtain the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle. The above-mentioned solution operations include: Obtain the current population and the historical global best fitness; where the initial population is the same as the initial population mentioned above, and the initial global best fitness is infinity; Based on the individual, the above equality constraints, inequality constraints, and the above power operation data, the current individual fitness of each individual in the current population is calculated; The minimum fitness among all current individual fitness values ​​is taken as the optimal fitness of the current population. Determine if the current number of iterations is not less than the preset maximum number of iterations; If the current number of iterations is not less than the preset maximum number of iterations, then the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle are determined based on the relationship between the current optimal fitness of the population and the historical global optimal fitness. Otherwise, if the current number of iterations is less than the preset maximum number of iterations, the individuals in the current population are updated. At the same time, if the current population's optimal fitness is less than the historical global optimal fitness, the historical global optimal fitness is updated based on the current population's optimal fitness.

[0095] In another preferred embodiment, the model solving unit includes: Fitness-determining sub-units and optimal duty cycle-determining sub-units; The fitness judgment subunit mentioned above is used to determine whether the current optimal fitness of the population is less than the historical global optimal fitness. The aforementioned optimal duty cycle determination subunit is used to determine the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle for individuals corresponding to the current optimal fitness, when the current population's optimal fitness is less than the historical global optimal fitness; otherwise, the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle for individuals corresponding to the historical global optimal fitness are used. It should be noted that the device embodiments described above are merely illustrative. The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationship between modules indicates that they have a communication connection, which can be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without creative effort. The above schematic diagram is merely an example of an extended phase-shift current optimization control device for a dual active bridge converter and does not constitute a limitation on an extended phase-shift current optimization control device for a dual active bridge converter. It may include more or fewer components than shown in the diagram, or combine certain components, or use different components.

[0096] Based on the above method embodiments, the present invention provides corresponding terminal device embodiments.

[0097] Another embodiment of the present invention provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the extended phase-shift current optimization control method for a dual active bridge converter described in any embodiment of the present invention.

[0098] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the device. The aforementioned terminal devices may be computing devices such as desktop computers, laptops, handheld computers, and cloud servers. These devices may include, but are not limited to, processors and memory. The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. This processor is the control center of the device, connecting various parts of the device via various interfaces and lines. The aforementioned memory can be used to store the aforementioned computer programs and / or modules. The aforementioned processor implements various functions of the aforementioned device by running or executing the computer programs and / or modules stored in the aforementioned memory, and by calling data stored in the memory. The aforementioned memory may mainly include a program storage area and a data storage area, wherein the program storage area may store the operating system, at least one application program required for a function, etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0099] Based on the above method embodiments, the present invention provides corresponding storage medium embodiments.

[0100] Another embodiment of the present invention provides a storage medium including a stored computer program, wherein, when the computer program is running, it controls the device where the storage medium is located to execute the extended phase-shift current optimization control method for a dual active bridge converter described in any embodiment of the present invention.

[0101] In this embodiment, the storage medium is a computer-readable storage medium, and the computer program includes computer program code, which may be in the form of source code, object code, executable file, or some intermediate form. The computer-readable medium may include any entity or device capable of carrying the computer program code, recording media, USB flash drive, portable hard drive, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc.

[0102] The above are preferred embodiments of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for optimized control of extended phase-shift current in a dual active bridge converter, characterized in that, include: Obtain the current power operation data of the dual active bridge converter; Based on the power operation data, an optimization model is constructed with the goal of minimizing the effective value of the inductor current, along with corresponding equality constraints and inequality constraints. The equality constraints indicate that the output power of the dual active bridge converter meets the preset active power reference value, and the inequality constraints are used to represent the constraint conditions that the inductor current needs to satisfy when all power devices achieve zero-voltage turn-on. Based on the power operation data, the optimization model is solved under the equality and inequality constraints to obtain the current optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle. Based on the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle, the bridge arm switches in the dual active bridge converter are driven to turn on and off in order to optimize the inductor current.

2. The extended phase-shift current optimization control method for a dual active bridge converter according to claim 1, characterized in that, The objective function of the optimization model is: In the formula, Indicates the effective value of the inductor current. Indicates the duty cycle of the inner phase shift. Indicates the duty cycle of the outgoing phase. The switching period is represented by t, where t represents time. Describe the objective function. This represents the piecewise function of inductor current.

3. The extended phase-shift current optimization control method for a dual active bridge converter according to claim 2, characterized in that, The equality constraint is: In the formula, P represents the output power of the dual active bridge converter. Indicates half a switching cycle. This indicates the AC port voltage of the primary-side full-bridge inverter. Indicates inductor current. Indicates the turns ratio of the primary and secondary sides of the transformer. This indicates the preset active power reference value.

4. The extended phase-shift current optimization control method for a dual active bridge converter according to claim 3, characterized in that, The inequality constraint is: In the formula, Indicates the start time of the half-cycle The inductor current at that time Indicates the voltage switching time corresponding to the inward shift. The inductor current at that time Indicates the voltage switching time corresponding to the outward shift. The inductor current at that time Indicates the end time of the half-cycle The inductor current at that time.

5. The extended phase-shift current optimization control method for a dual active bridge converter according to claim 4, characterized in that, The step of solving the optimization model based on the power operation data, under the equality and inequality constraints, to obtain the current optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle includes: An initial population is generated based on the preset inner phase duty cycle threshold range and the preset outer phase duty cycle threshold range; wherein, the population includes several individuals, each individual representing a parameter combination consisting of an inner phase duty cycle and an outer phase duty cycle; The optimization model is repeatedly solved based on the power operation data, the initial population, the equality constraints, and the inequality constraints to obtain the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle. The solution operation includes: Obtain the current population and the historical global optimal fitness; wherein, the initial population is the initial population, and the initial global optimal fitness is infinity; Based on the individual, the equality constraints, the inequality constraints, and the power operation data, the current individual fitness of each individual in the current population is calculated; The minimum fitness among all current individual fitness values ​​is taken as the optimal fitness of the current population. Determine if the current number of iterations is not less than the preset maximum number of iterations; If the current number of iterations is not less than the preset maximum number of iterations, then the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle are determined based on the relationship between the current optimal fitness of the population and the historical global optimal fitness. Otherwise, if the current number of iterations is less than the preset maximum number of iterations, the individuals in the current population are updated. At the same time, if the current population's optimal fitness is less than the historical global optimal fitness, the historical global optimal fitness is updated based on the current population's optimal fitness.

6. The extended phase-shift current optimization control method for a dual active bridge converter according to claim 5, characterized in that, Based on the relationship between the current optimal fitness of the population and the historical global optimal fitness, the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle are determined, including: Determine whether the current optimal fitness of the population is less than the historical global optimal fitness; If the current optimal fitness of the population is less than the historical global optimal fitness, the inner phase shift duty cycle and the outer phase shift duty cycle of the individual corresponding to the current optimal fitness of the population are taken as the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle, respectively. Otherwise, the inner phase duty cycle and outer phase duty cycle of the individual corresponding to the historical global optimal fitness are taken as the optimal inner phase duty cycle and the optimal outer phase duty cycle, respectively.

7. An extended phase-shift current optimization control device for a dual active bridge converter, characterized in that, include: The system includes a power operation data acquisition module, a model building module, a duty cycle calculation module, and an inductor current optimization module. The power operation data acquisition module is used to acquire the current power operation data of the dual active bridge converter; The model building module is used to build an optimization model based on the power operation data, with the goal of minimizing the effective value of the inductor current, as well as corresponding equality constraints and inequality constraints; wherein, the equality constraints indicate that the output power of the dual active bridge converter meets the preset active power reference value, and the inequality constraints are used to indicate the constraint conditions that the inductor current needs to meet when all power devices achieve zero-voltage turn-on; The duty cycle solving module is used to solve the optimization model based on the power operation data and under the equality and inequality constraints to obtain the current optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle. The inductor current optimization module is used to drive the bridge arm switches in the dual active bridge converter to turn on and off according to the optimal inner phase shift duty cycle and the optimal outer phase shift duty cycle, so as to optimize the inductor current.

8. The extended phase-shift current optimization control device for a dual active bridge converter according to claim 7, characterized in that, The objective function of the optimization model is constructed as follows: In the formula, Indicates the effective value of the inductor current. Indicates the duty cycle of the inner phase shift. Indicates the duty cycle of the outgoing phase. The switching period is represented by t, where t represents time. Describe the objective function. This represents the piecewise function of inductor current.

9. A terminal device, characterized in that, The system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor, when executing the computer program, implements an extended phase-shift current optimization control method for a dual active bridge converter as described in any one of claims 1 to 6.

10. A storage medium, characterized in that, The storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device where the storage medium is located to perform an extended phase-shift current optimization control method for a dual active bridge converter as described in any one of claims 1 to 6.

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