Magnetic suspension flywheel energy storage and super capacitor series-parallel high-efficiency energy management system

Abstract

The invention discloses a magnetic suspension flywheel energy storage and super capacitor hybrid efficient energy management system, and relates to the field of magnetic suspension flywheel energy storage, the system is composed of a magnetic suspension flywheel energy storage device, a super capacitor energy storage device and an energy management module, and efficient cooperative work is realized through a dynamic power distribution strategy. The energy management module comprises a load demand detection unit, an energy storage state monitoring unit and a dynamic distribution control unit, the dynamic distribution control unit adopts a fuzzy control algorithm, and the charge-discharge proportion is adjusted in real time based on flywheel rotating speed deviation, super capacitor voltage deviation and load power fluctuation frequency. When the load power exceeds a threshold value, the super capacitor is preferentially called to respond to the instantaneous high power requirement, and the flywheel is switched to improve the efficiency when the low power is continuous. The system is also configured with an LSTM adaptive algorithm to dynamically optimize a threshold value, and safety and stability are guaranteed in combination with mechanisms such as active cooling, over-temperature protection and redundant backup.

Description

Technical Field

[0001] The present invention relates to the field of magnetic levitation flywheel energy storage, and in particular to a high-efficiency energy management system that combines magnetic levitation flywheel energy storage with supercapacitors. Background Art

[0002] As a highly efficient energy storage technology, flywheel energy storage has attracted extensive attention and research due to its advantages, including high energy density, fast response time, long service life, low maintenance costs, and environmental friendliness. Patent document CN118554621A, which describes a flywheel energy storage power station management system, demonstrates significant potential in the energy storage field.

[0003] However, the existing flywheel energy storage array has many problems in practical application. Taking the existing technology mentioned in CN118554621A, a flywheel energy storage power station management system, as an example, the existing flywheel energy storage array usually communicates directly with the flywheel controller, measurement and control device and fire protection device through the energy management system (refer to the patent document in the patent document). Figure 1 This communication method is slow and can only achieve basic AGC (Automatic Generation Control) / AVC (Automatic Voltage Control) functions, failing to meet the complex and ever-changing demands of power systems. This results in a limited number of application scenarios for flywheel energy storage arrays, hindering their full potential and leading to low utilization rates.

[0004] Furthermore, existing energy management systems often lack effective dynamic allocation strategies when coordinating the operation of different energy storage devices. These systems are unable to optimize charging and discharging power distribution in real time based on actual load demand and energy storage status, making it difficult to maximize system efficiency. Furthermore, monitoring and protection of energy storage devices are also inadequate, failing to fully guarantee the safe and stable operation of energy storage systems. Therefore, developing a system that can combine the advantages of multiple energy storage systems to achieve efficient energy management is of great practical significance. Summary of the Invention

[0005] The purpose of the present invention is to provide a high-efficiency energy management system that combines magnetic levitation flywheel energy storage with supercapacitors to solve the problems raised in the above background technology.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a high-efficiency energy management system that combines magnetic levitation flywheel energy storage with supercapacitors, comprising:

[0007] a magnetically suspended flywheel energy storage device that supports the flywheel rotor via magnetically suspended bearings to reduce mechanical friction losses and is configured to store and release kinetic energy;

[0008] a supercapacitor energy storage device configured to store and quickly release electrical energy to handle instantaneous high power demands;

[0009] Energy management module, which includes:

[0010] Load demand detection unit, used to monitor the instantaneous power demand and power fluctuation frequency of the system load in real time;

[0011] An energy storage status monitoring unit is used to collect in real time the rotation speed and kinetic energy storage capacity of the magnetic levitation flywheel energy storage device and the voltage, current and residual charge of the supercapacitor energy storage device;

[0012] a dynamic allocation control unit, which dynamically adjusts the charge and discharge power allocation ratio of the magnetic levitation flywheel energy storage device and the supercapacitor energy storage device according to the output signals of the load demand detection unit and the energy storage status monitoring unit through a preset optimization algorithm to maximize system efficiency;

[0013] The dynamic allocation control unit preferentially calls upon the electric energy of the supercapacitor energy storage device when the load power demand exceeds a preset threshold; and preferentially calls upon the kinetic energy of the magnetic levitation flywheel energy storage device when the load power demand is lower than the preset threshold and the duration exceeds a predetermined time;

[0014] The energy management module is further configured to dynamically adjust the charge and discharge power of the magnetic levitation flywheel energy storage device and the voltage of the supercapacitor energy storage device according to the rotation speed of the magnetic levitation flywheel energy storage device and the voltage of the supercapacitor energy storage device to maintain system energy balance and reduce energy loss.

[0015] Furthermore, the dynamic allocation control unit adopts a fuzzy control algorithm, and the fuzzy control algorithm includes:

[0016] The input variables are the speed deviation (Δω) of the magnetic levitation flywheel energy storage device, the voltage deviation (ΔV) of the supercapacitor energy storage device, and the load power fluctuation frequency (f). The fuzzy set of Δω is low deviation, medium deviation, and high deviation; the fuzzy set of ΔV is low deviation, medium deviation, and high deviation; and the fuzzy set of f is low frequency, medium frequency, and high frequency.

[0017] The output variable is the power distribution ratio P of the magnetic levitation flywheel energy storage device flywheel / P total , its fuzzy sets are low proportion, medium proportion, and high proportion;

[0018] The fuzzy rule base contains 9 rules.

[0019] Furthermore, the preset threshold is dynamically adjusted in the following manner:

[0020] Adopting an adaptive learning algorithm based on a long short-term memory network (LSTM), the system takes as input historical load power data (hourly power values for the past 24 hours) and real-time load forecast data (power forecast values for the next hour).

[0021] The output adjusted threshold formula is:

[0022]

[0023] Among them, α is the learning rate (0.1≤α≤0.3)P predict_peak To predict the peak power, P historical_avg is the historical average power.

[0024] Furthermore, the magnetic suspension bearing of the magnetic suspension flywheel energy storage device is an electromagnetic suspension bearing, which includes:

[0025] Eight sets of electromagnetic coils are evenly distributed along the circumference of the bearing. Each set of coils adjusts the current through a PWM controller to maintain the suspension of the flywheel rotor.

[0026] The active cooling system includes an annular heat sink and an axial fan. When the bearing temperature sensor detects that the temperature exceeds 60°C, the fan is started to force heat dissipation and the coolant flow rate is increased to 120% of the rated value.

[0027] Furthermore, the dynamic adjustment is achieved by the following formula:

[0028]

[0029] Among them, E flywheel is the current kinetic energy of the magnetic levitation flywheel E total is the total energy storage of the system (E total =E flywheel +E cap ), E cap The remaining energy of the supercapacitor And require P flywheel ≤0.8·P flywheel_max To avoid overloading the flywheel.

[0030] Furthermore, the energy storage status monitoring unit includes:

[0031] Thermocouple temperature sensor, used to monitor the supercapacitor casing temperature, triggering over-temperature protection when the temperature exceeds 65°C;

[0032] The internal resistance monitoring circuit calculates the equivalent internal resistance (R eq =ΔV / 1A, when R eq When the resistance is ≥25mΩ, reduce the upper limit of supercapacitor charge and discharge power to 70% of the rated value.

[0033] Furthermore, the system further comprises:

[0034] The grid interface module includes a three-phase full-bridge inverter that supports AC / DC bidirectional conversion, with a priority of grid power supply > flywheel energy storage > supercapacitor;

[0035] The redundant protection module switches to the backup energy storage unit (such as a backup supercapacitor bank or backup flywheel) within 0.2 seconds when it detects that the flywheel speed is lower than 80% of the set value or the supercapacitor voltage is lower than 2V / cell for more than 5 seconds.

[0036] Furthermore, the weight coefficient w of the fuzzy control algorithm flywheel and w cap Dynamically adjust according to the following rules:

[0037] Efficiency flywheel is the current efficiency of the flywheel (calculated by the speed decay rate);

[0038] Cycle cap Cycle is the number of cycles of the supercapacitor. cap_max is the rated cycle life.

[0039] Furthermore, the flywheel rotor of the magnetic levitation flywheel energy storage device is made of carbon fiber / epoxy resin composite material (density 1.6g / cm 3 , tensile strength 4,500MPa), which:

[0040] Energy storage density of not less than 500Wh / kg (verified by kinetic energy calculation at speeds of 10,000 to 100,000 rpm);

[0041] The rotor diameter is 0.8 meters, the maximum centrifugal stress is 70% of the material's tensile strength, and the structural integrity is verified through ANSYS simulation.

[0042] Furthermore, the supercapacitor energy storage device is composed of 12 3,000F / 2.7V capacitor units connected in parallel and equipped with an active balancing circuit, including:

[0043] MOSFET switch array, when the voltage difference between any two capacitor units exceeds 3%, the current is balanced through resistor shunting;

[0044] The balancing trigger cycle is once every 10 seconds, and the maximum current for a single balancing is 0.5A, ensuring that the voltage deviation of the capacitor unit is ≤1%.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] The energy management module of this patent monitors the instantaneous power demand of the system load, the frequency of power fluctuations, and the status of the energy storage device in real time. Using a preset optimization algorithm, it dynamically allocates the charge and discharge power between the magnetic levitation flywheel energy storage device and the supercapacitor energy storage device. When the load power demand exceeds a preset threshold, the supercapacitor is prioritized. The dynamic allocation control unit utilizes a fuzzy control algorithm, taking the speed deviation of the magnetic levitation flywheel energy storage device, the voltage deviation of the supercapacitor energy storage device, and the load power fluctuation frequency as input variables, and outputs the power allocation ratio for the magnetic levitation flywheel energy storage device. The preset threshold is dynamically adjusted using an adaptive learning algorithm based on a long short-term memory (LSTM) network. Combining historical load power data with real-time load forecast data, the system can more rationally switch energy storage device calls based on actual load conditions, improving system adaptability and stability. The energy storage status monitoring unit monitors the temperature and internal resistance of the supercapacitor in real time. When the temperature is too high or the internal resistance is too high, appropriate protection measures are triggered to reduce the upper limit of charge and discharge power, ensuring the safety of the supercapacitor. The redundant protection module quickly switches to the backup energy storage unit in the event of abnormal flywheel speed or supercapacitor voltage, improving system reliability and fault tolerance. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0048] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0049] See also Figure 1 The present invention provides a technical solution: a high-efficiency energy management system that combines magnetic levitation flywheel energy storage with supercapacitors, comprising:

[0050] A magnetically suspended flywheel energy storage device, which supports the flywheel rotor via magnetic bearings to reduce mechanical friction losses and is configured to store and release kinetic energy. Eight sets of electromagnetic coils are evenly distributed along the circumference of the bearings, and each set of coils uses a PWM controller to regulate current to maintain the flywheel rotor's levitation.

[0051] The active cooling system installed on the bearing includes annular heat sinks and axial fans. When the bearing temperature sensor detects that the temperature exceeds 60°C, the fan is started to force heat dissipation and the coolant flow rate is increased to 120% of the rated value.

[0052] Each set of coils uses a PWM controller to precisely regulate the current, maintaining the stable suspension of the flywheel rotor. In actual operation, when the flywheel rotor deflects slightly, the PWM controller quickly adjusts the current in the corresponding coil, generating the appropriate electromagnetic force to return the rotor to its equilibrium position. The active cooling system is equipped with annular heat sinks and an axial fan. When the bearing temperature sensor detects a temperature exceeding 60°C, the axial fan activates for forced cooling, while the coolant flow rate is increased to 120% of the rated value, ensuring that the bearing operates within the appropriate temperature range and guaranteeing the stability and reliability of the device.

[0053] The supercapacitor energy storage device is configured to store and rapidly release electrical energy to meet instantaneous high power demands. Composed of 12 3,000F / 2.7V capacitor cells connected in parallel, it possesses the characteristics of storing and rapidly releasing electrical energy, effectively handling instantaneous high power demands. To ensure the consistency and stability of the capacitor cells, an active balancing circuit is configured. When the voltage difference between any two capacitor cells exceeds 3%, the MOSFET switch array activates, balancing the current through resistor shunting. The balancing trigger cycle is set to once every 10 seconds, with a maximum current of 0.5A per single balancing, ensuring that the capacitor cell voltage deviation is ≤1%. In multiple charge and discharge experiments, this balancing circuit effectively prevents performance degradation and shortened lifespan of the capacitor cells due to large voltage differences.

[0054] Energy management module, which includes:

[0055] Load demand detection unit, used to monitor the instantaneous power demand and power fluctuation frequency of the system load in real time;

[0056] The energy storage status monitoring unit collects real-time data on the speed and kinetic energy storage of the magnetic levitation flywheel energy storage device, as well as the voltage, current, and residual charge of the supercapacitor energy storage device. It uses high-precision power sensors and frequency monitoring equipment to monitor the instantaneous power demand and power fluctuation frequency of the system load in real time. These sensors convert the collected signals into electrical signals and transmit them to the subsequent control unit for processing.

[0057] A dynamic allocation control unit, which dynamically adjusts the charge and discharge power distribution ratio of the magnetic levitation flywheel energy storage device and the supercapacitor energy storage device based on the output signals of the load demand detection unit and the energy storage status monitoring unit through a preset optimization algorithm to maximize system efficiency;

[0058] Among them, the dynamic allocation control unit gives priority to calling the electric energy of the supercapacitor energy storage device when the load power demand exceeds the preset threshold; when the load power demand is lower than the preset threshold and the duration exceeds the predetermined time, the kinetic energy of the magnetic levitation flywheel energy storage device is given priority;

[0059] The energy storage status monitoring unit includes:

[0060] Thermocouple temperature sensor, used to monitor the supercapacitor casing temperature, triggering over-temperature protection when the temperature exceeds 65°C;

[0061] The internal resistance monitoring circuit calculates the equivalent internal resistance (R eq =ΔV / 1A, when P eq When the resistance is ≥25mΩ, reduce the upper limit of supercapacitor charge and discharge power to 70% of the rated value.

[0062] The energy management module is further configured to dynamically adjust the charge and discharge power of the magnetic levitation flywheel energy storage device and the voltage of the supercapacitor energy storage device according to the rotation speed of the magnetic levitation flywheel energy storage device and the voltage of the supercapacitor energy storage device to maintain system energy balance and reduce energy loss.

[0063] The dynamic allocation control unit adopts fuzzy control algorithm, which includes:

[0064] The input variables are the speed deviation (Δω) of the magnetic levitation flywheel energy storage device, the voltage deviation (ΔV) of the supercapacitor energy storage device, and the load power fluctuation frequency (f). The fuzzy set of Δω is low deviation, medium deviation, and high deviation; the fuzzy set of ΔV is low deviation, medium deviation, and high deviation; and the fuzzy set of f is low frequency, medium frequency, and high frequency.

[0065] The output variable is the power distribution ratio P of the magnetic levitation flywheel energy storage device flywheel / P total , its fuzzy sets are low proportion, medium proportion, and high proportion;

[0066] The fuzzy rule base contains nine rules. These rules are derived from extensive experimental data and theoretical analysis. For example, when the speed deviation is low, the voltage deviation is low, and the load power fluctuation frequency is low, the fuzzy rule base will allocate a lower proportion of power to the magnetic levitation flywheel energy storage device.

[0067] The preset threshold is dynamically adjusted in the following ways:

[0068] Adopting an adaptive learning algorithm based on a long short-term memory network (LSTM), the system takes as input historical load power data (hourly power values for the past 24 hours) and real-time load forecast data (power forecast values for the next hour).

[0069] The output adjusted threshold formula is:

[0070]

[0071] Among them, α is the learning rate (0.1≤α≤0.3)P predict_peak To predict the peak power, P historical_avg is the historical average power.

[0072] The magnetic suspension bearing of the magnetic suspension flywheel energy storage device is an electromagnetic suspension bearing, which includes:

[0073] Dynamic adjustment is achieved through the following formula:

[0074]

[0075] Among them, E flywheel is the current kinetic energy of the magnetic levitation flywheel E total is the total energy storage of the system (E total =E flywheel +E cap ), E cap The remaining energy of the supercapacitor And require P flywheel ≤0.8·P flywheel_max To avoid overloading the flywheel.

[0076] The system also includes:

[0077] The grid interface module, which includes a three-phase full-bridge inverter, supports bidirectional AC / DC conversion, prioritizing grid power > flywheel energy storage > supercapacitors. When the grid is functioning normally, grid power is used first. In the event of a grid failure or power shortage, flywheel energy storage and supercapacitor energy storage are sequentially utilized based on system requirements. In the event of a grid outage, the flywheel energy storage device quickly activates to provide power to critical loads. When the flywheel energy storage runs low, the supercapacitor energy storage device promptly replenishes power, ensuring continuous system operation.

[0078] The redundant protection module switches to the backup energy storage unit (such as a backup supercapacitor bank or backup flywheel) within 0.2 seconds when it detects that the flywheel speed is lower than 80% of the set value or the supercapacitor voltage is lower than 2V / cell for more than 5 seconds. This effectively ensures the stability and reliability of the system and avoids system paralysis due to energy storage device failure.

[0079] The weight coefficient w of the fuzzy control algorithm flywheel and w cap Dynamically adjust according to the following rules:

[0080] Efficiency flywheel is the current efficiency of the flywheel (calculated by the speed decay rate);

[0081] Cycle cap Cycle is the number of cycles of the supercapacitor. cap_max is the rated cycle life.

[0082] The flywheel rotor of the magnetic levitation flywheel energy storage device is made of carbon fiber / epoxy resin composite material (density 1.6g / cm 3 , tensile strength 4,500MPa), which:

[0083] Energy storage density of not less than 500Wh / kg (verified by kinetic energy calculation at speeds of 10,000 to 100,000 rpm);

[0084] The rotor diameter is 0.8 meters, the maximum centrifugal stress is 70% of the material's tensile strength, and the structural integrity is verified through ANSYS simulation.

[0085] The supercapacitor energy storage device consists of 12 3,000F / 2.7V capacitor units connected in parallel and equipped with an active balancing circuit, including:

[0086] MOSFET switch array, when the voltage difference between any two capacitor units exceeds 3%, the current is balanced through resistor shunting;

[0087] The balancing trigger cycle is once every 10 seconds, and the maximum current for a single balancing is 0.5A, ensuring that the voltage deviation of the capacitor unit is ≤1%.

Claims

1. A high-efficiency energy management system that combines magnetic levitation flywheel energy storage with supercapacitors, characterized in that: include: a magnetically suspended flywheel energy storage device that supports the flywheel rotor via magnetically suspended bearings to reduce mechanical friction losses and is configured to store and release kinetic energy; a supercapacitor energy storage device configured to store and quickly release electrical energy to handle instantaneous high power demands; Energy management module, which includes: Load demand detection unit, used to monitor the instantaneous power demand and power fluctuation frequency of the system load in real time; An energy storage status monitoring unit is used to collect in real time the rotation speed and kinetic energy storage capacity of the magnetic levitation flywheel energy storage device and the voltage, current and residual charge of the supercapacitor energy storage device; a dynamic allocation control unit, which dynamically adjusts the charge and discharge power allocation ratio of the magnetic levitation flywheel energy storage device and the supercapacitor energy storage device according to the output signals of the load demand detection unit and the energy storage status monitoring unit through a preset optimization algorithm to maximize system efficiency; The dynamic allocation control unit preferentially calls upon the electric energy of the supercapacitor energy storage device when the load power demand exceeds a preset threshold; and preferentially calls upon the kinetic energy of the magnetic levitation flywheel energy storage device when the load power demand is lower than the preset threshold and the duration exceeds a predetermined time; The energy management module is further configured to dynamically adjust the charge and discharge power of the magnetic levitation flywheel energy storage device and the voltage of the supercapacitor energy storage device according to the rotation speed of the magnetic levitation flywheel energy storage device and the voltage of the supercapacitor energy storage device to maintain system energy balance and reduce energy loss.

2. The high-efficiency energy management system of magnetic levitation flywheel energy storage and supercapacitor hybrid according to claim 1 is characterized in that: The dynamic allocation control unit adopts a fuzzy control algorithm, which includes: The input variables are the speed deviation (Δω) of the magnetic levitation flywheel energy storage device, the voltage deviation (ΔV) of the supercapacitor energy storage device, and the load power fluctuation frequency (f). The fuzzy set of Δω is low deviation, medium deviation, and high deviation; the fuzzy set of ΔV is low deviation, medium deviation, and high deviation; and the fuzzy set of f is low frequency, medium frequency, and high frequency. The output variable is the power distribution ratio P of the magnetic levitation flywheel energy storage device flywheel / P total , its fuzzy sets are low proportion, medium proportion, and high proportion; The fuzzy rule base contains 9 rules.

3. The high-efficiency energy management system of magnetic levitation flywheel energy storage and supercapacitor hybrid according to claim 1 is characterized in that: The preset threshold is dynamically adjusted in the following ways: Adopting an adaptive learning algorithm based on a long short-term memory network (LSTM), the system takes as input historical load power data (hourly power values for the past 24 hours) and real-time load forecast data (power forecast values for the next hour). The output adjusted threshold formula is: Among them, α is the learning rate (0.1≤α≤0.3)P predict_peak To predict the peak power, P historical_avg is the historical average power.

4. The high-efficiency energy management system of magnetic levitation flywheel energy storage and supercapacitor hybrid according to claim 1 is characterized in that: The magnetic suspension bearing of the magnetic suspension flywheel energy storage device is an electromagnetic suspension bearing, which includes: Eight sets of electromagnetic coils are evenly distributed along the circumference of the bearing. Each set of coils adjusts the current through a PWM controller to maintain the suspension of the flywheel rotor. The active cooling system installed on the bearing includes annular heat sinks and axial fans. When the bearing temperature sensor detects that the temperature exceeds 60°C, the fan is started to force heat dissipation and the coolant flow rate is increased to 120% of the rated value.

5. The high-efficiency energy management system of magnetic levitation flywheel energy storage and supercapacitor hybrid according to claim 1 is characterized in that: The dynamic adjustment is achieved through the following formula: Among them, E flywheel is the current kinetic energy of the magnetic levitation flywheel E total is the total energy storage of the system (E total =E flywheel +E cap ), E cap The remaining energy of the supercapacitor And require P flywheel ≤0.8·P flywheel_max To avoid overloading the flywheel.

6. The high-efficiency energy management system of magnetic levitation flywheel energy storage and supercapacitor hybrid according to claim 1 is characterized in that: The energy storage status monitoring unit includes: Thermocouple temperature sensor, used to monitor the supercapacitor casing temperature, triggering over-temperature protection when the temperature exceeds 65°C; The internal resistance monitoring circuit calculates the equivalent internal resistance (R eq =ΔV / 1A, when R eq When the resistance is ≥25mΩ, reduce the upper limit of supercapacitor charge and discharge power to 70% of the rated value.

7. The high-efficiency energy management system of magnetic levitation flywheel energy storage and supercapacitor hybrid according to claim 1 is characterized in that: The system further comprises: The grid interface module includes a three-phase full-bridge inverter that supports AC / DC bidirectional conversion, with a priority of grid power supply > flywheel energy storage > supercapacitor; The redundant protection module switches to the backup energy storage unit (such as a backup supercapacitor bank or backup flywheel) within 0.2 seconds when it detects that the flywheel speed is lower than 80% of the set value or the supercapacitor voltage is lower than 2V / cell for more than 5 seconds.

8. The high-efficiency energy management system of magnetic levitation flywheel energy storage and supercapacitor hybrid according to claim 2 is characterized in that: The weight coefficient w of the fuzzy control algorithm flywheel and w cap Dynamically adjust according to the following rules: Efficiency flywheel is the current efficiency of the flywheel (calculated by the speed decay rate); Cycle cap The number of cycles that the supercapacitor has cycled, cycle cap_max is the rated cycle life.

9. The high-efficiency energy management system of magnetic levitation flywheel energy storage and supercapacitor hybrid according to claim 1 is characterized in that: The flywheel rotor of the magnetic levitation flywheel energy storage device is made of carbon fiber / epoxy resin composite material (density 1.6g / cm 3 , tensile strength 4,500MPa), which: Energy storage density of not less than 500Wh / kg (verified by kinetic energy calculation at speeds of 10,000 to 100,000 rpm); The rotor diameter is 0.8 meters, the maximum centrifugal stress is 70% of the material's tensile strength, and the structural integrity is verified through ANSYS simulation.

10. The high-efficiency energy management system of magnetic levitation flywheel energy storage and supercapacitor hybrid according to claim 1 is characterized in that: The supercapacitor energy storage device is composed of 12 3,000F / 2.7V capacitor units connected in parallel and equipped with an active balancing circuit, including: MOSFET switch array, when the voltage difference between any two capacitor units exceeds 3%, the current is balanced through resistor shunting; The balancing trigger cycle is once every 10 seconds, and the maximum current for a single balancing is 0.5A, ensuring that the voltage deviation of the capacitor unit is ≤1%.

Images