Unmanned aerial vehicle hybrid power system energy management method based on fuzzy double closed-loop control

Abstract

The invention discloses an unmanned aerial vehicle hybrid power supply system energy management method based on fuzzy double closed-loop control in the technical field. An unmanned aerial vehicle hybrid power supply system comprises a hydrogen fuel cell, a lithium battery and a double active bridge circuit, and the hydrogen fuel cell and the lithium battery serve as energy sources of the hybrid power supply system; the dual-active bridge circuit is used for connecting a hydrogen fuel cell and a lithium battery and transmitting energy to an unmanned aerial vehicle load, the energy management method comprises a fuzzy power control outer ring and a fuzzy PI current control inner ring, the fuzzy power control outer ring dynamically distributes power according to a power signal required by the unmanned aerial vehicle load, a power error signal and a lithium battery charge state, and the fuzzy PI current control inner ring controls the power to be output. The fuzzy PI current control inner loop generates an accurate driving signal according to the battery power and the voltage ratio after fuzzy distribution, a switching device of the dual active bridge circuit is driven to be switched on, energy transmission is achieved, and the problems that in existing unmanned aerial vehicle energy management, the cruising ability is insufficient, and the energy utilization efficiency is low can be effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned aerial vehicle power supply, and in particular to a unmanned aerial vehicle power supply system and a management method thereof. Background Art

[0002] With the rapid development of UAV technology, its application in logistics, transportation, environmental monitoring and other fields is becoming more and more extensive. However, insufficient endurance and low energy management efficiency have become the key bottlenecks restricting the performance improvement of UAVs. Most traditional UAVs use a single lithium battery as a power source. Although lithium batteries have high energy conversion efficiency and good dynamic response characteristics, their energy density is limited and it is difficult to meet the needs of long-duration missions. In addition, the state of charge (SOC) of the lithium battery changes continuously during the flight. How to efficiently manage the power output of the power supply to meet the load requirements of the UAV while extending the battery life is a technical problem that needs to be solved urgently. The prior art discloses an independent input dual-channel-winding series dual active bridge circuit and its control method, and its publication number is: CN118381336A.

[0003] In recent years, hybrid power systems have gradually attracted attention due to their complementary advantages. The system is usually composed of hydrogen fuel cells and lithium batteries. Hydrogen fuel cells have the advantages of high energy density and long battery life, but the dynamic response speed is slow; lithium batteries have fast charging and discharging capabilities and good dynamic response characteristics, but the energy density is relatively low. Combining the two can give full play to their respective advantages and significantly improve the endurance and energy utilization efficiency of drones. However, the energy management method of hybrid power systems is the core issue to achieve their efficient operation. Traditional energy management methods mostly use fixed ratio allocation or rule-based control methods. These methods are difficult to adapt to the complex and changeable flight conditions of drones, and cannot achieve the optimal allocation of energy, resulting in low system efficiency and may even affect the flight safety of drones. In terms of power conversion circuits, although the traditional dual active bridge (DAB) circuit can realize bidirectional energy transmission, its topology and control method have limitations when multiple power inputs. For example, when multiple power sources are connected, the traditional DAB circuit has low energy transmission efficiency and cannot give full play to the potential of the hybrid power system, resulting in insufficient system reliability and difficulty in meeting the energy management needs of high-performance drones. The existing UAV power system has many deficiencies in energy density, dynamic response and energy management efficiency, which limits the application of UAVs in long-flight and complex mission scenarios. Therefore, an efficient hybrid power energy management method is urgently needed to achieve dynamic coordination between hydrogen fuel cells and lithium batteries through advanced control strategies and optimized circuit topology, improve energy transmission efficiency and system reliability, and thus significantly improve the endurance and overall performance of UAVs. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a hybrid power supply system and energy management method for a UAV based on fuzzy dual closed-loop control. The output power of hydrogen fuel cells and lithium batteries is dynamically allocated through the synergistic effect of a fuzzy power control outer loop and a fuzzy PI current control inner loop. In combination with an improved independent input dual-channel-winding series dual active bridge circuit, efficient energy transmission and management are achieved, thereby significantly improving the endurance and overall performance of the UAV.

[0005] The object of the present invention is achieved as follows: an energy management method for a hybrid power system of an unmanned aerial vehicle based on fuzzy dual closed-loop control, wherein the hybrid power system of the unmanned aerial vehicle includes a hydrogen fuel cell, a lithium battery, and a dual active bridge circuit, wherein the hydrogen fuel cell and the lithium battery serve as energy sources of the hybrid power system; the dual active bridge circuit is used to connect the hydrogen fuel cell and the lithium battery and transmit energy to the unmanned aerial vehicle load, characterized in that the energy management method includes a fuzzy power control outer loop and a fuzzy PI current control inner loop, wherein the fuzzy power control outer loop dynamically allocates power according to the power signal required by the unmanned aerial vehicle load, the power error signal and the charge state of the lithium battery, and the fuzzy PI current control inner loop generates an accurate drive signal according to the battery power and voltage ratio after fuzzy allocation, drives the switch device of the dual active bridge circuit to turn on, and realizes energy transmission.

[0006] Furthermore, the input of the fuzzy power control outer loop includes the UAV load demand power signal, the power error signal and the lithium battery SOC, and the output is the hydrogen fuel cell power and the lithium battery power; the input of the fuzzy PI current control inner loop includes the battery power and voltage ratio after fuzzy allocation as the reference current, as well as the deviation and deviation change rate of the lithium battery current, and the output is an adjustment value for generating a precise drive signal to drive the switching device of the independent input dual-channel-winding series dual active bridge circuit to turn on, thereby realizing energy transmission.

[0007] Furthermore, the steps of the fuzzy power control outer loop are as follows:

[0008] a. Take the UAV load demand power signal, power error signal and lithium battery SOC as input variables and transform them into fuzzy sets through fuzzy processing;

[0009] b. Establish fuzzy rules based on the UAV working conditions and expert experience, perform fuzzy reasoning on the input variables, and determine the power allocation ratio of hydrogen fuel cells and lithium batteries;

[0010] c. Defuzzify the results of fuzzy reasoning to obtain specific hydrogen fuel cell power and lithium battery power.

[0011] Furthermore, the steps for establishing the fuzzy PI current control inner loop are as follows:

[0012] a. The ratio of battery power and voltage after fuzzy allocation is used as the reference current, and the deviation of the battery current from the reference current and the deviation change rate are used as input variables;

[0013] b. Fuzzify the input variables through the fuzzy controller and perform fuzzy reasoning in combination with fuzzy rules;

[0014] c. Adjust the parameters of the PI controller according to the results of fuzzy reasoning to generate accurate driving signals;

[0015] d. The driving signal is used to control the switching devices of the independent input dual-channel winding series dual active bridge circuit to conduct, thereby realizing energy transmission.

[0016] Compared with the prior art, the present invention has the following beneficial effects:

[0017] The present invention adopts a hybrid power system of hydrogen fuel cells and lithium batteries, giving full play to the advantages of high energy density of hydrogen fuel cells and rapid response of lithium batteries, significantly extending the flight time of the UAV and meeting the requirements of long-flight missions.

[0018] The present invention adopts a fuzzy double closed-loop control strategy to dynamically allocate power according to the load demand of the UAV and the status of the lithium battery, optimize energy utilization efficiency, and adapt to complex flight conditions. The improved dual active bridge circuit is used to optimize the power conversion efficiency, improve the reliability and stability of the system, and ensure energy supply during long-term flight.

[0019] The fuzzy control of the present invention is combined with PI control to achieve fast and accurate energy distribution and transmission, and improve the responsiveness and maneuverability of the UAV in different flight stages. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0021] Figure 1 Schematic diagram of the hybrid power system architecture of the present invention.

[0022] Figure 2 Schematic diagram of the independent input dual-channel-winding series dual active bridge circuit of the present invention.

[0023] Figure 3 Schematic diagram of the fuzzy double closed-loop control energy management strategy of the present invention.

[0024] Figure 4Schematic diagram of power relationship of PI control method in the embodiment.

[0025] Figure 5 Schematic diagram of hydrogen consumption by PI control method in the embodiment.

[0026] Figure 6 Schematic diagram of power relationship of fuzzy double closed-loop control method in an embodiment of the present invention.

[0027] Figure 7 Schematic diagram of hydrogen consumption of the fuzzy double closed-loop control method in an embodiment of the present invention.

[0028] Figure 2 Symbolic names in:

[0029]

[0030] Figure 3 Symbolic names in:

[0031] DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] A hybrid power energy management method for UAV based on fuzzy double closed-loop control, such as Figure 1 As shown, the hybrid power system includes a hydrogen fuel cell, a lithium battery, and a dual active bridge (DAB) circuit; the hydrogen fuel cell and the lithium battery serve as energy sources for the hybrid power system; the dual active bridge (DAB) circuit is used to connect the hydrogen fuel cell and the lithium battery and transmit energy to the UAV load; the energy management method dynamically allocates the output power of the hydrogen fuel cell and the lithium battery according to the load power demand of the UAV and the state of charge (SOC) of the lithium battery using a fuzzy double closed-loop energy management method, the fuzzy double closed-loop energy management method includes a fuzzy power control outer loop and a fuzzy PI current control inner loop, the outer loop dynamically allocates power according to the UAV load power demand signal, the power error signal and the lithium battery SOC, the inner loop generates a precise drive signal according to the battery power and voltage ratio after fuzzy allocation, drives the switch device of the DAB circuit to turn on, and realizes energy transmission.

[0034] Specifically, Figure 2As shown, the dual active bridge (DAB) circuit (see the background technology document with publication number: CN118381336A) is composed of the DC end of the battery side full bridge circuit of the 1# dual active bridge circuit and the DC end of the battery side full bridge circuit of the 2# dual active bridge circuit to form a dual channel port connected to the hydrogen fuel cell and lithium batteries The midpoint of the bridge arm of the 1# dual active bridge full bridge circuit and the midpoint of the bridge arm of the 2# dual active bridge full bridge circuit are connected to the battery side windings of the corresponding high frequency transformers Tr1 and Tr2, the load side windings of the high frequency transformers Tr1 and Tr2 are connected in series, and one end of the load side winding after the series connection is connected to the resonant inductor , DC blocking capacitor The resonant inductor and the DC blocking capacitor are connected in series with the load-side full-bridge circuit. The DC blocking capacitor is connected to the midpoint of one arm of the load-side full-bridge circuit. The midpoint of the other arm of the load-side full-bridge circuit is connected to the other end of the series connection of the load-side winding. The DC end of the load-side full-bridge circuit is connected to the drone load. .

[0035] Further, such as Figure 3 As shown, the fuzzy power control outer loop selects the UAV load demand power signal , the error signal between the required power and the actual power , lithium battery As input, hydrogen fuel cell power And lithium battery power The inner loop selects the ratio of battery power and voltage after fuzzy allocation as the reference current , and the lithium battery current Deviation Deviation change rate As input, adjust the value , As the output, after adjustment, an accurate driving signal is generated to drive the switch tube in the DAB circuit to turn on, thereby realizing energy transmission.

[0036] Furthermore, the steps of the fuzzy power control outer loop are as follows:

[0037] a. The UAV load demand power signal , power error signal And the lithium battery SOC is used as the input variable, which is converted into a fuzzy set through fuzzification processing.

[0038] Specifically, first determine the technical parameter indicators of the drone hybrid power system as shown in Table 1:

[0039] Table 1 Main technical parameters of UAV

[0040]

[0041] According to the main technical parameters of the UAV, an outer loop fuzzy power allocator is designed. The Gaussian membership function is selected for its input and output variables, and the basic domain and fuzzy set are selected as follows: The domain is [0, 5] kW, divided into three fuzzy sets: PS (positive small), PM (positive medium), and PB (positive large), and the power error signal The domain is [-5, 5] kW, divided into five fuzzy sets: NB (large negative), NS (small negative), ZO (zero), PS, and PB. The state of charge of lithium batteries The domain is [20%, 90%], divided into three fuzzy sets: PS, PM, and PB. The output power of hydrogen fuel cells The domain is [0, 6] kW, divided into three fuzzy sets: PS, PM, and PB. The output power of lithium batteries The domain is [-3, 5]kW, which is divided into five fuzzy sets: NM, NS, ZO, PS, and PB.

[0042] b. Establish fuzzy rules based on the UAV operating conditions and expert experience, perform fuzzy reasoning on the input variables, and determine the power allocation ratio of hydrogen fuel cells and lithium batteries.

[0043] Specifically, first determine the flight conditions of the drone:

[0044] (1) In takeoff mode, the drone has a high power demand. At this time, the hydrogen fuel cell provides peak power, and the insufficient power is supplemented by the lithium battery:

[0045] (2) In cruise mode, the UAV operates normally, the output power of the hydrogen fuel cell is basically the same as the required power, and the lithium battery acts as a backup power source. When encountering gusts of wind, the lithium battery responds quickly and replenishes power.

[0046] (3) In light load mode, such as when the drone is unloading or descending, the power demand is low. The hydrogen fuel cell not only powers the drone but also charges the lithium battery.

[0047] According to the UAV flight conditions and expert experience, IF-THEN fuzzy conditional statements are selected and fuzzy rules are formulated as shown in Tables 2, 3, and 4:

[0048] Table 2 = PS , Fuzzy rule table

[0049]

[0050] Table 3 = PM , Fuzzy control rule table

[0051]

[0052] Table 4 =PB , Fuzzy control rule table

[0053]

[0054] c. Defuzzify the results of fuzzy reasoning to obtain specific hydrogen fuel cell power and lithium battery power.

[0055] Specifically, according to the fuzzy control rule table, we can get The output linguistic variables are defuzzified by weighted average method:

[0056]

[0057] in, For each element in the domain, is the membership degree of the fuzzy set after fuzzification, which is used as the weight coefficient of the corresponding element. The fuzzy quantity after defuzzification is then refined through the proportional factor to obtain the specific hydrogen fuel cell power And lithium battery power The actual value of .

[0058] Furthermore, the steps for establishing the inner loop of the fuzzy PI current control are as follows:

[0059] a. Use the battery power and voltage ratio after fuzzy allocation as the reference current , the deviation of lithium battery current from reference current and the rate of change of deviation as input variables;

[0060] b. Fuzzy processing of input variables is performed through fuzzy controller, and fuzzy reasoning is performed in combination with fuzzy rules.

[0061] Specifically, an inner loop fuzzy PI regulation current controller is designed, and its input and output variables are both triangular membership functions; when the input is small, the membership function is steeper to improve resolution and sensitivity; when the input is large, the membership function is flat to ensure system stability; the current deviation of the hydrogen fuel cell is selected The basic domain is [-72, 72], and the current deviation change rate The basic domain is [-5, 5], and the current deviation of the lithium battery The basic domain is [-42, 42], and the current deviation change rate The basic domain is [-5, 5]; for lithium batteries, the fuzzy output is defined as , the fuzzy subset language value is {NB, NM, NS, ZO, PS, PM, PB}, and the output fuzzy domain is {-3, -2, -1, 0, 1, 2, 3}.

[0062] Specifically, according to expert experience: when formulating a rule table, we should take into account both stability and response speed. Ensure the response speed, then reduce it slightly to ensure stability without reducing the adjustment speed, and then increase it again in the later stage to reduce the error and improve the accuracy; select a smaller value at the beginning of the response Speed ​​up the response, place it in the middle during the adjustment process to avoid affecting stability, and improve it later In order to reduce static error and improve accuracy, the corresponding fuzzy control rules are formulated as shown in Table 5:

[0063] Table 5 Fuzzy control rule table

[0064]

[0065] c. Adjust the parameters of the PI controller according to the results of fuzzy reasoning to generate accurate driving signals;

[0066] Specifically, the result of fuzzy reasoning is obtained by defuzzification using the weighted average method, that is, the control signal output by the fuzzy PI controller of the corresponding channel is used as the modulation signal of the phase-shift PWM modulator. The pulse control signal generated by the phase-shift PWM modulator is then used to control the on and off of the switch tube in the DAB circuit after passing through the driving circuit, thereby realizing energy transmission.

[0067] d. The drive signal is used to control the conduction of the switch devices of the independent input dual-channel-winding series dual active bridge circuit to achieve energy transmission.

[0068] The UAV hybrid power system model and control strategy were built in the MATLAB environment. Figure 4 and Figure 5 The power distribution diagram and hydrogen consumption diagram of the traditional PI control method are given. The hydrogen consumption is 8.65g. Figure 6 and Figure 7 The power distribution diagram and hydrogen consumption diagram of the fuzzy double closed-loop control method of the present invention are given. The hydrogen consumption is 7.75g. Compared with the traditional control strategy, the average energy conversion efficiency of the hydrogen fuel cell under the fuzzy double closed-loop energy management strategy reaches 56%. The hydrogen consumption is reduced from 8.65g to 7.75g, a decrease of about 15%.

[0069] From the above description, it can be seen that the UAV hybrid power energy management method based on fuzzy double closed-loop control proposed in the present invention has the following main advantages:

[0070] (1) Significantly improve the endurance. The hybrid power system of hydrogen fuel cells and lithium batteries fully utilizes the advantages of high energy density of hydrogen fuel cells and rapid response of lithium batteries, significantly extending the endurance of UAVs and meeting the requirements of long-flight missions.

[0071] (2) Efficient dynamic energy management, using a fuzzy double closed-loop control strategy to dynamically allocate power according to the UAV's load requirements and lithium battery status, optimize energy utilization efficiency, and adapt to complex flight conditions.

[0072] (3) Enhanced system reliability and stability: The improved dual active bridge (DAB) circuit optimizes the power conversion efficiency, improves the system reliability and stability, and ensures energy supply during long-term flight.

[0073] The above embodiments are only used to help understand the method and core idea of ​​the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made to the present invention without departing from the principles of the present invention, and these improvements and modifications also fall within the scope of protection of the claims of the present invention.

Claims

1. An energy management method for a hybrid power system of an unmanned aerial vehicle based on fuzzy double closed-loop control, wherein the hybrid power system of the unmanned aerial vehicle comprises a hydrogen fuel cell, a lithium battery, and a dual active bridge circuit, wherein the hydrogen fuel cell and the lithium battery serve as energy sources of the hybrid power system; the dual active bridge circuit is used to connect the hydrogen fuel cell and the lithium battery and transmit energy to the unmanned aerial vehicle load, characterized in that: The energy management method includes a fuzzy power control outer loop and a fuzzy PI current control inner loop. The fuzzy power control outer loop dynamically allocates power according to the UAV load demand power signal, the power error signal and the lithium battery charge state. The fuzzy PI current control inner loop generates an accurate driving signal according to the battery power and voltage ratio after fuzzy allocation, drives the switching device of the dual active bridge circuit to turn on, and realizes energy transmission.

2. The energy management method of the hybrid power system of a UAV based on fuzzy double closed-loop control according to claim 1 is characterized in that: The input of the fuzzy power control outer loop includes the UAV load demand power signal, the power error signal and the lithium battery SOC, and the output is the hydrogen fuel cell power and the lithium battery power; the input of the fuzzy PI current control inner loop includes the battery power and voltage ratio after fuzzy allocation as the reference current, as well as the deviation and deviation change rate of the lithium battery current, and the output is an adjustment value for generating a precise drive signal to drive the switching device of the independent input dual-channel-winding series dual active bridge circuit to turn on, thereby realizing energy transmission.

3. The energy management method of the hybrid power system of a UAV based on fuzzy double closed-loop control according to claim 2 is characterized in that: The steps of the fuzzy power control outer loop are as follows: a. Take the UAV load demand power signal, power error signal and lithium battery SOC as input variables and transform them into fuzzy sets through fuzzy processing; b. Establish fuzzy rules based on the UAV working conditions and expert experience, perform fuzzy reasoning on the input variables, and determine the power allocation ratio of hydrogen fuel cells and lithium batteries; c. Defuzzify the results of fuzzy reasoning to obtain specific hydrogen fuel cell power and lithium battery power.

4. The energy management method of the hybrid power system of a UAV based on fuzzy double closed-loop control according to claim 3 is characterized in that: The steps for establishing the fuzzy PI current control inner loop are as follows: a. The ratio of battery power and voltage after fuzzy allocation is used as the reference current, and the deviation of the battery current from the reference current and the deviation change rate are used as input variables; b. Fuzzify the input variables through the fuzzy controller and perform fuzzy reasoning in combination with fuzzy rules; c. Adjust the parameters of the PI controller according to the results of fuzzy reasoning to generate accurate driving signals; d. The driving signal is used to control the switching devices of the independent input dual-channel winding series dual active bridge circuit to conduct, thereby realizing energy transmission.

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