Photovoltaic energy storage control method and vehicle-mounted sunshade thereof

Abstract

The application discloses a photovoltaic energy storage control method and a vehicle-mounted sunshade thereof, and the method comprises the following steps: acquiring voltage and current data of a flexible solar panel and a hybrid energy storage module to obtain input data; calculating an output reference current value of the solar panel according to the input data and generating a PWM signal; and controlling a converter module according to the PWM signal. The vehicle-mounted sunshade comprises a reel, a flexible solar panel, a sunshade cloth, a converter module and a hybrid energy storage module, the reel is connected with the sunshade cloth, the lower surface of the sunshade cloth is provided with a retractable metal bending arm, the upper surface of the sunshade cloth is provided with the flexible solar panel, the flexible solar panel is connected with the converter module, and the converter module is connected with the hybrid energy storage module. The control method can greatly reduce the calculation amount of the controller and improve the control efficiency, and the vehicle-mounted sunshade has high convenience and feasibility. The application can be widely applied in the field of vehicle-mounted photovoltaic devices.

Description

Technical Field

[0001] The present invention relates to the field of vehicle-mounted photovoltaic equipment, and in particular to a photovoltaic energy storage control method and a vehicle-mounted sunshade. Background Art

[0002] The RV market is currently experiencing rapid growth in my country. Due to their specialized uses and market positioning, RVs require far more electricity than conventional cars. However, due to technical bottlenecks in battery storage and geographical restrictions, RVs often face power shortages. Photovoltaic power generation utilizes the photoelectric effect of semiconductors to convert solar energy into electricity for loads. Due to its green, environmentally friendly, and geographically independent advantages, PV power is widely used in the automotive, communications, and transportation sectors, alleviating power shortages in RVs. However, the intermittent nature and low efficiency of PV power generation have hindered the commercial adoption of PV equipment. Therefore, the development of PV equipment for RVs is crucial for addressing this power shortage.

[0003] Existing energy storage control methods are mostly based on PID control. As a classic control algorithm, PID control suffers from slow dynamic response, large overshoot, and narrow bandwidth. In RV energy storage and use, the intermittent nature of photovoltaic power generation and the plug-and-play nature of loads involve dynamic system processes. Therefore, solutions based on PID controllers have many limitations. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a photovoltaic energy storage control method and a vehicle-mounted awning thereof, which can greatly reduce the calculation amount of the controller and improve the control efficiency. The vehicle-mounted awning has high convenience and feasibility.

[0005] The first technical solution adopted by the present invention is: a photovoltaic energy storage control method, comprising the following steps:

[0006] Obtain voltage and current data of the flexible solar panel and hybrid energy storage module to obtain input data;

[0007] Calculate the output reference current value of the solar panel according to the input data and generate a PWM signal;

[0008] The converter module is controlled according to the PWM signal.

[0009] Furthermore, the step of processing the input data to obtain the PWM signal based on the maximum power point tracking control method specifically includes:

[0010] Calculate the output power of the flexible solar panel based on the input data and define the system error;

[0011] Get trigger conditions based on actual demand and output curve of photovoltaic cells;

[0012] In the photovoltaic controller, if it is determined that the system error meets the trigger condition, the MPPT controller will work, update the output current reference value signal, and calculate the PWM signal by the model predictive controller. If it is determined that the system error does not meet the trigger condition, the MPPT controller will not work, maintain the output current reference value signal at the previous moment, and calculate the PWM signal by the model predictive controller.

[0013] In the hybrid energy storage system controller, if it is determined that the system error meets the trigger conditions, the model predictive controller will work, update the output current reference value signal, and the hysteresis controller will calculate the PWM signal. If it is determined that the system error does not meet the trigger conditions, the model predictive controller will not work, maintain the output current reference value signal at the previous moment, and the hysteresis controller will calculate the PWM signal.

[0014] Furthermore, the triggering conditions of the PV controller are expressed as follows:

[0015]

[0016] In the above formula, e PV,i (k) represents the photovoltaic control system error, P represents the output power, u i represents the output voltage of the i-th solar panel, T represents the ambient temperature, and λ represents the adjustment factor.

[0017] Furthermore, the triggering conditions of the hybrid energy storage system controller are expressed as follows:

[0018] ||e HESS (t)||≤αγ -1 ||x(t)||

[0019] In the above formula, ||e HESS (t)|| and ||x(t)|| are the norms of the corresponding variables, and α and γ are κ-type functions.

[0020] The second technical solution adopted by the present invention is: a vehicle-mounted awning, including a reel, a flexible solar panel, a sunshade cloth, a converter module and a hybrid energy storage module, the reel is connected to the sunshade cloth, the lower surface of the sunshade cloth is provided with a retractable metal flex arm, the upper surface of the sunshade cloth is installed with a flexible solar panel, the flexible solar panel is connected to the converter module, and the converter module is connected to the hybrid energy storage module.

[0021] Furthermore, the reel includes a rotating shaft, a mounting plate, a metal shell and a worm gear, the rotating shaft is connected to the fixed end of the sunshade cloth, the mounting plate is fixedly installed on the outside of the car, the metal shell is connected to the mounting plate, a placement bin is provided inside the metal shell, and the worm gear is installed on the side of the metal shell.

[0022] Furthermore, the flexible solar panel includes a waterproof wiring port and a flexible solar cell assembly, and the waterproof wiring port connects the flexible solar cell assembly in series and parallel and then connects it to the converter.

[0023] Furthermore, the converter module includes a single-inductor-multiple-input-single-output Boost converter, a bidirectional converter, a controller and a sensor. The input end of the single-inductor-multiple-input-single-output Boost converter is connected to the solar panel, the output end of the single-inductor-multiple-input-single-output Boost converter is connected to the load, the input end of the controller is connected to the output end of the sensor, and the output end of the controller is respectively connected to the input end of the single-inductor-multiple-input-single-output Boost converter and the input end of the bidirectional converter.

[0024] Furthermore, the hybrid energy storage module includes a battery, a capacitor and a load, the battery is connected to the load through a bidirectional converter, and the capacitor is connected to the load through a bidirectional converter.

[0025] The beneficial effects of the present invention are as follows: the present invention arranges flexible solar panels on the vehicle-mounted awning, which greatly increases the illuminated area, improves the charging power of the battery, and is easy to store and place, simple and feasible to operate. By adopting a single inductor, multi-input and single-output circuit topology structure, the number of components is greatly reduced, thereby reducing costs; in addition, the new maximum power point tracking control (MPPT) method can reduce the adverse effects of local shading of flexible solar panels on the power generation power of photovoltaic equipment, effectively reduce output power fluctuations, and can greatly reduce the calculation amount of the controller, thereby improving control efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of the steps of a photovoltaic energy storage control method of the present invention;

[0027] Figure 2 This is a structural schematic diagram of a vehicle-mounted awning according to the present invention;

[0028] Figure 3 is a partial circuit diagram of a specific embodiment of the present invention;

[0029] Figure 4 is a flowchart of a photovoltaic controller according to a specific embodiment of the present invention;

[0030] Figure 5 It is a flowchart of a hybrid energy storage controller according to a specific embodiment of the present invention;

[0031] Description of the accompanying drawings: 1. Mounting plate; 2. Through slot; 3. Metal shell; 4. Scroll; 5. Buckle; 6. Metal flex arm; 7. Flexible solar panel; 8. Sunshade; 10. Support rod; 11. Worm gear; 12. Battery; 13. Capacitor. DETAILED DESCRIPTION

[0032] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. The step numbers in the following embodiments are provided for ease of description only and do not limit the order of the steps. The order of execution of the steps in the embodiments can be adaptively adjusted based on the understanding of those skilled in the art.

[0033] Reference Figure 1 The present invention provides a photovoltaic energy storage control method, which includes the following steps:

[0034] S1. Obtain voltage and current data of the flexible solar panel and the hybrid energy storage module to obtain input data;

[0035] S2. Calculate the output reference current value of the solar panel based on the input data and generate a PWM signal;

[0036] S2.1. Calculate the output power of the flexible solar panel based on the input data and define the system error.

[0037] Specifically, the voltage U and current I at the output end of each flexible solar panel are measured by sensors, and the output power P = UI of the flexible solar panel at this time is calculated. The system error at this time is defined as:

[0038]

[0039] Because the maximum power point Therefore

[0040]

[0041] S2.2. Determine trigger conditions based on actual demand and the output curve of the photovoltaic cell;

[0042] Specifically, the triggering conditions of the photovoltaic controller are as follows:

[0043]

[0044] In the above formula, e PV,i (k) represents the photovoltaic control system error, P represents the output power, u i represents the output voltage of the i-th solar panel, T represents the ambient temperature, and λ represents the adjustment factor.

[0045] The discrete-time state-space equation of the single-inductor-multiple-input-single-output Boost converter is:

[0046]

[0047] Among them, T s is the sampling time of the system; u out ,i out is the output voltage and current of the single-inductor-multiple-input-single-output Boost converter; L is the size of the single inductor; C is the size of the filter capacitor; q is the switching state of the single-inductor-multiple-input-single-output Boost converter; is the input voltage of the single-inductor-multiple-input-single-output Boost converter, q j ,v j They are the switching states and output voltages of the respective switching devices of the solar panels.

[0048] According to the idea of ​​phase-shift average filter, multiple iterations of discrete time state space equation can be calculated to obtain u out (k+m),u out (k+2m)…u out (k+Nm). Where N and m are natural numbers, here N=5, m=3; the design evaluation function is:

[0049] The discrete-time state space model of the hybrid energy storage system is:

[0050]

[0051] in:

[0052]

[0053] The design evaluation function is: J2(k,x)=u(k) T Ru(k)+(y(k)-y * ) T G(y(k)-y * )+J(k+1,Ax+Bu)

[0054] Where V bat 、V sc Indicates the voltage of the battery and supercapacitor, I batref , I scref , I dcbus Represent the current reference values ​​of the battery, supercapacitor and DC side respectively, I lastbatref , I lastscref They represent the current reference values ​​of the battery and supercapacitor at the previous moment respectively, and the R and G matrices represent the weight matrices.

[0055] An event-triggered controller is used to reduce unnecessary computational complexity. Similar to the photovoltaic power generation system, another event-triggered controller is designed to reduce the computational complexity of the model predictive control. Its design process is as follows:

[0056] e HESS (t) = x(t) - x(t i )

[0057]

[0058] Among them, x(t) is the observed value of the hybrid energy storage system at the current moment, x(t i ) is the observed value of the hybrid energy storage system when the last event is triggered, t et The preset sampling time for the event-triggered controller.

[0059] According to event-triggered control theory, in order to ensure the stability of the input state of the control system, the error e HESS (t) Need to meet:

[0060] ||e HESS (t)||≤αγ -1 ||x(t)||

[0061] where ||e HESS (t)|| and ||x(t)|| are the norms of the corresponding variables, and α and γ are κ-type functions.

[0062] From the discrete time state space equation of the hybrid energy storage system, we can get:

[0063]

[0064] ||A1x(t)||+||B1u(t)||=||A1x(t i )-A1e HESS (t)||+||B1u(t i )||≤||A1e HESS (t)||+||A1x(t i )||+||B1u(t i )||≤||A1||||e HESS (t)||+||A1x(t i )||+||B1u(t i )||

[0065] By defining ψ(t)=||e HESS (t)||+(||A1x(t i )||+||B1u(t i )||)||A1|| -1 ,available:

[0066]

[0067] Note HESS (t i )=0, so ψ(t i )=(||A1x(t i )||+||B1u(t i )||)||A1|| -1

[0068]

[0069] Therefore, we can obtain the following inequality:

[0070]

[0071] The final triggering conditions of the hybrid energy storage system are:

[0072] The coefficients λ and t et It can be used to adjust the balance between system performance and computational load.

[0073] S2.3. In the photovoltaic controller, if it is determined that the system error meets the trigger condition, the MPPT controller will operate, update the output current reference value signal, and calculate the PWM signal using the model predictive controller. If it is determined that the system error does not meet the trigger condition, the MPPT controller will not operate, maintain the output current reference value signal at the previous moment, and calculate the PWM signal using the model predictive controller.

[0074] S2.4. In the hybrid energy storage system controller, if it is determined that the system error meets the trigger condition, the model predictive controller will work, update the output current reference value signal, and the hysteresis controller will calculate the PWM signal. If it is determined that the system error does not meet the trigger condition, the model predictive controller will not work, maintain the output current reference value signal at the previous moment, and the hysteresis controller will calculate the PWM signal.

[0075] Specifically, the event-triggered controller collects current and voltage signals and determines whether to trigger the model predictive controller by calculating and comparing the system error with the designed trigger conditions. If the trigger conditions are met, the model predictive controller begins to operate and updates the controller's output signal. If the trigger conditions are not met, the model predictive controller is suspended, and the controller's output signal remains consistent with the output signal at the previous moment, thereby reducing the controller's computational complexity.

[0076] The iterative learning controller adopts the PD type iterative learning control law, namely:

[0077] u n+1 (k)=u n (k)+KP e n (k)+K D (e n+1 (k)-e n (k))

[0078] e n+1 (k) = I dcbusref (k)-I dcbus (k),

[0079]

[0080] Among them G P , G D They are proportional learning gain and differential learning gain respectively. Generally, G D than G P Several orders of magnitude larger.

[0081] Specifically, the iterative learning controller is part of the hybrid energy storage controller and is used to calculate the DC current reference value that can maintain the DC side voltage stability of the hybrid energy storage system. The iterative learning controller includes two parts: the PID controller and the iterative learning law. The DC bus side voltage reference value is subtracted from the DC bus side voltage actual value to obtain the system error e(k). After the limit processing, it is calculated by the iterative learning law to obtain the output u k,ilc , and the output of the PID controller is u k,pid , and finally the output of the iterative learning controller is u k =u k,pid +u k,ilc In this example, u k is the DC bus side current reference value I dcbusref .

[0082] S3. Control the converter module according to the PWM signal.

[0083] Specifically, the voltage and current data of the flexible solar panel and hybrid energy storage module are transmitted to the controller in real time through sensors. The controller processes the output voltage and current data online according to the corresponding control algorithm to obtain a PWM signal. The signal output end of the controller transmits the PWM signal to the signal input end of each converter.

[0084] like Figure 2As shown, a vehicle-mounted awning includes a reel 4, a flexible solar panel 7, a sunshade cloth 8, a converter module and a hybrid energy storage module. The reel 4 is connected to the sunshade cloth 8, and the lower surface of the sunshade cloth 8 is provided with a retractable metal bent arm 6. The reel 4 includes a rotating shaft, a mounting plate 1, a metal shell 3 and a worm gear 12. The rotating shaft is connected to the fixed end of the sunshade cloth 8, and the mounting plate 1 is fixedly installed on the outside of the car. The metal shell 3 is connected to the mounting plate 1, and a placement bin is provided inside the metal shell 3. The worm gear 12 is installed on the side of the metal shell 3. The upper surface of the sunshade cloth 8 is installed with a flexible solar panel 7, and the flexible solar panel 7 is connected to the converter module, and the converter module is connected to the hybrid energy storage module.

[0085] Specifically, the storage compartment is used to store a flexible solar panel 7 and a sunshade cloth 8. During use, the user rotates the worm gear's buckle 5 on the ground using a rocker, causing the flexible solar panel 7 and sunshade cloth 8 to slide out of the through slot 2 and fully unfold. During this process, the metal flex arms 6 mounted beneath the metal housing 3 gradually straighten from their folded state to support the sunshade cloth 8. Furthermore, to alleviate the supporting pressure of the metal flex arms 6 and extend their service life, support rods 10 are installed at the two corners of the movable side of the sunshade cloth 8 to provide support after it is fully unfolded.

[0086] As a further preferred embodiment, the flexible solar panel includes a waterproof wiring port and a flexible solar cell assembly, and the waterproof wiring port connects the flexible solar cell assembly in series and parallel and then connects it to the converter.

[0087] As a further preferred embodiment, refer to Figure 2 The circuit diagram includes a hybrid energy storage module and a converter module. The converter module includes a single-inductor-multiple-input-single-output Boost converter, a bidirectional converter, a controller and a sensor. The input end of the single-inductor-multiple-input-single-output Boost converter is connected to the solar panel, the output end of the single-inductor-multiple-input-single-output Boost converter is connected to the load, the input end of the controller is connected to the output end of the sensor, and the output end of the controller is respectively connected to the input end of the single-inductor-multiple-input-single-output Boost converter and the input end of the bidirectional converter. The hybrid energy storage module includes a battery 13, a capacitor 14 and a load. The battery 13 is connected to the load through the bidirectional converter, and the capacitor 14 is connected to the load through the bidirectional converter.

[0088] Specifically, the hybrid energy storage module is used to improve the power quality on the DC side. The battery 13 has high energy density and low power density, while the capacitor 14 is a supercapacitor with high power density and low energy density. The battery 13 and supercapacitor 14 are connected to the DC side via a converter. The DC side voltage is 72V, and the rated voltages of the battery 13 and supercapacitor 14 are both 36V. When the RV solar awning is in the stowed state, the load power is entirely provided by the hybrid energy storage module. When the RV solar awning is operating, the generated electricity is first supplied to the DC side load, and the power shortage (or surplus) is supplemented (or absorbed) by the hybrid energy storage module. When the DC side power fluctuates due to load jumps and fluctuations in photovoltaic power generation, the controller calculates the current DC side power shortage or surplus based on current and voltage data and distributes the unmatched power portion to the hybrid energy storage module according to control rules. The battery in the hybrid energy storage module responds to the low-frequency power portion of the fluctuating power, while the supercapacitor responds to the high-frequency power portion of the fluctuating power, thereby maintaining the stability of the DC side voltage and improving the power supply quality.

[0089] Reference Figure 4 The duty cycle of the single-inductor-multiple-input-single-output boost converter is related to its respective current reference value. The current reference value is calculated by the controller using the maximum power tracking method based on the current and voltage conditions of each solar panel. The actual current needs to be processed by the moving average filter (MAF) and then subtracted from the current reference value to obtain the error value. The duty cycle of the converter connected to the DC side is calculated by the model predictive controller. ref,1 ,i ref,2 …i ref,n-1 is the output current reference value of each flexible solar panel; i1, i2…i n-1 is the actual output current value of each flexible solar panel; q1, q2…q n is the duty cycle of each multi-input port, and q' and q are the duty cycles of two complementary switching devices.

[0090] Reference Figure 4 The hybrid energy storage module controller includes an event-triggered controller, a model predictive controller, an iterative learning controller, and a hysteresis controller. The event-triggered controller reduces the number of calculations in the model predictive controller; the iterative learning controller generates a DC-side reference current value; the model predictive controller generates output current reference values ​​for the battery and supercapacitor; and the hysteresis controller compares the actual output current with the current reference value to generate a control signal.

[0091] Reference Figure 5The hybrid energy storage module controller includes an event-triggered controller, a model predictive controller, an iterative learning controller, and a hysteresis controller. The event-triggered controller reduces the number of calculations in the model predictive controller; the iterative learning controller generates a DC-side reference current value; the model predictive controller generates output current reference values ​​for the battery and supercapacitor; and the hysteresis controller compares the actual output current with the current reference value to generate a PWM signal.

[0092] The iterative learning controller consists of two parts: the PID controller and the iterative learning law. The system error e(k) is obtained by subtracting the DC bus voltage reference value from the DC bus voltage actual value. After the limit processing, the output u is obtained by the iterative learning law calculation. k,ilc , and the output of the PID controller is u k,pid , and finally the output of the iterative learning controller is u k =u k,pid +u k,ilc In this example, u k is the DC bus side current reference value I dcbusref .

[0093] To ensure that multiple solar panels can operate simultaneously near their respective maximum power points, a single-inductor, multi-input, single-output boost converter is used. The output of each solar panel is connected to the input of the single-inductor, multi-input, single-output boost converter, which in turn is connected to the DC load. The output current and voltage data of each solar panel are transmitted to the controller input via sensors. The controller calculates the current reference value for each input port using a maximum power point tracking control method, and uses this to calculate the duty cycle of the corresponding switching device. The resulting duty cycle is pulse-width modulated, and the resulting switching control signal is output to the input of each converter.

[0094] The working process of the present invention is described in detail below: (1) When the RV is parked, after using the hand crank to connect the worm gear device of the RV awning, rotate the hand crank to slide the sunshade cloth and the flexible solar panel out of the slide slot until they are fully unfolded. (2) After the RV awning is arranged, under sunlight, the flexible solar panel starts to work, and the output current and voltage are transmitted to the controller through the sensor. The controller calculates the output current reference value of each solar panel based on the voltage and current data, and obtains the duty cycle through the PI link and logic processing. The duty cycle is pulse-width modulated to obtain a switching signal. The obtained switching signal is transmitted through the signal output end of the controller to the signal receiving end of each converter to control the on and off of the switching device, thereby obtaining the maximum photovoltaic power generation power. The photovoltaic power generation energy will be directly supplied to the DC side load for use. (3) Due to the uncertainty of changes in environmental factors such as light intensity and temperature, the photovoltaic power generation power will fluctuate. During operation, the controller collects and processes data such as the PV power generation voltage and current, the DC side voltage and current, the battery voltage and current, and state of charge (SOC), as well as the supercapacitor voltage and current and SOC, to generate control signals for each converter. The control principle is as follows: When there is a DC side power surplus—that is, when the PV power generation exceeds the current load power—the low-frequency portion of the surplus power is absorbed by the battery, while the high-frequency portion is absorbed by the supercapacitor, and vice versa. This solves the problem of power mismatch on the DC side, maintaining DC side voltage stability.

[0095] The contents of the above method embodiments are all applicable to this embodiment. The functions specifically implemented by this embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0096] The above is a specific description of the preferred implementation of the present invention, but the invention is not limited to the embodiments. Those skilled in the art can make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of this application.

Claims

1. A photovoltaic energy storage control method, characterized in that: The following steps are involved: Obtain voltage and current data of the flexible solar panel and the hybrid energy storage module to obtain input data; Calculate the output reference current value of the solar panel according to the input data and generate a PWM signal; Control the converter module according to the PWM signal; The step of calculating the output reference current value of the solar panel according to the input data and generating a PWM signal specifically includes: Calculate the output power of the flexible solar panel based on the input data and define the system error; Get trigger conditions based on actual demand and output curve of photovoltaic cells; In the photovoltaic controller, if it is determined that the system error meets the trigger condition, the MPPT controller will work, update the output current reference value signal, and calculate the PWM signal by the model predictive controller. If it is determined that the system error does not meet the trigger condition, the MPPT controller will not work, maintain the output current reference value signal at the previous moment, and calculate the PWM signal by the model predictive controller. In the hybrid energy storage system controller, if it is determined that the system error meets the trigger condition, the model predictive controller will work, update the output current reference value signal, and the hysteresis controller will calculate the PWM signal. If it is determined that the system error does not meet the trigger condition, the model predictive controller will not work, the output current reference value signal at the previous moment will be maintained, and the hysteresis controller will calculate the PWM signal. The trigger conditions of the PV controller are as follows: In the above formula, e PV,i (k) represents the photovoltaic control system error, P represents the output power, u i represents the output voltage of the i-th solar panel, T represents the ambient temperature, and λ represents the adjustment factor; The triggering conditions of the hybrid energy storage system controller are as follows: ||e HESS (t)||≤αγ -1 ||x(t)|| In the above formula, ||e HESS x(t)|| and ‖x(t)|| are the norms of the corresponding variables, and α and γ are κ-type functions.

2. A vehicle-mounted awning, characterized in that: A photovoltaic energy storage control method according to claim 1 is applied, comprising a reel, a flexible solar panel, a sunshade cloth, a converter module, and a hybrid energy storage module, wherein the reel is connected to the sunshade cloth, a retractable metal flex arm is provided on the lower surface of the sunshade cloth, a flexible solar panel is mounted on the upper surface of the sunshade cloth, the flexible solar panel is connected to the converter module, and the converter module is connected to the hybrid energy storage module; The discrete-time state-space equation of the single-inductor-multiple-input-single-output Boost converter is: Among them, T s is the sampling time of the system; u out ,i out is the output voltage and current of the single-inductor-multiple-input-single-output Boost converter; L is the size of the single inductor; C is the size of the filter capacitor; q is the switching state of the single-inductor-multiple-input-single-output Boost converter; is the input voltage of the single-inductor-multiple-input-single-output Boost converter, q j ,v j They are the switching states and output voltages of the respective switching devices of the solar panels.

3. The vehicle-mounted awning according to claim 2, characterized in that: The reel includes a rotating shaft, a mounting plate, a metal shell and a worm gear. The rotating shaft is connected to the fixed end of the sunshade cloth. The mounting plate is fixedly installed on the outside of the car. The metal shell is connected to the mounting plate. A placement bin is provided inside the metal shell. The worm gear is installed on the side of the metal shell.

4. The vehicle-mounted awning according to claim 3, characterized in that: The flexible solar panel comprises a waterproof connection port and a flexible solar cell assembly. The waterproof connection port connects the flexible solar cell assembly in series and parallel and then connects it to the converter.

5. The vehicle-mounted awning according to claim 4, characterized in that: The converter module includes a single-inductor-multiple-input-single-output Boost converter, a bidirectional converter, a controller and a sensor. The input end of the single-inductor-multiple-input-single-output Boost converter is connected to the solar panel, the output end of the single-inductor-multiple-input-single-output Boost converter is connected to the load, the input end of the controller is connected to the output end of the sensor, and the output end of the controller is respectively connected to the input end of the single-inductor-multiple-input-single-output Boost converter and the input end of the bidirectional converter.

6. The vehicle-mounted awning according to claim 5, characterized in that: The hybrid energy storage module includes a battery, a capacitor and a load. The battery is connected to the load through a bidirectional converter, and the capacitor is connected to the load through a bidirectional converter.

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