652 results about "High-pass filter" patented technology

The invention relates to the technical field of image enhancement, in particular to an archive restoration system based on image enhancement, and the system comprises a high-frequency detail enhancement module which receives a damaged archive image, processes high-frequency information through a high-pass filter, and obtains a high-frequency processed image; the high frequency processed image is sharpened while maintaining smoothness of the low frequency region, generating a detail enhanced image. According to the method, the high-frequency information of the damaged archive image is independently processed, the detail part in the image is independently extracted and sharpened, and meanwhile, the low-frequency region is kept smooth, so that the detail definition of the image and the overall visual naturalness are synchronously improved; and in the image texture repairing process, the texture of the undamaged area is analyzed, and key texture features are extracted and expanded, so that the texture and the pattern of the damaged area are accurately reconstructed, and the integrity and the authenticity of the image structure and the content are ensured.

A system and method for enhancing or restoring audio data utilizing an artificial intelligence module, and more particularly utilizing deep neural networks and generative adversarial networks. The system and method are both able to train the artificial intelligence module to provide for different format and other characteristic-specific transforms for determining how to restore audio to source quality and even beyond. The present invention includes the steps of acquiring source data, pre-processing the source data, implementing the artificial intelligence module, indexing the data, applying transforms, and optimizing the data for a particular audio modality.

The invention discloses a multi-mode hybrid energy storage cooperative control method and system for a megawatt-level network-building type energy storage power station, and the method comprises the steps: S1, collecting the frequency, voltage amplitude and phase of a power grid, and the charge state and temperature of each energy storage branch, and generating real-time monitoring data; s2, determining an operation mode of the energy storage power station based on a comparison result between the frequency deviation and the voltage deviation in the real-time monitoring data and a preset threshold value; s3, based on the operation mode of the energy storage power station, performing double-layer decomposition on the power instruction through a high-pass filter and a low-pass filter to generate a super-capacitor power instruction and a lithium battery power instruction; s4, generating an internal potential amplitude and a phase angle by adopting a virtual synchronous machine algorithm; and S5, on the basis of the amplitude and the phase angle of the internal potential and the detection result of the power grid connection state, executing switching control of a network construction type control mode or a network following type control mode. The millisecond-second level multi-time scale power optimal distribution is realized; self-adaptive inertia and voltage support is carried out; and island / grid-connected seamless switching is realized.

The invention relates to a method for predicting cochlear hearing loss based on pure tone induced SFOAE, which comprises the following steps of: extracting a stimulation frequency otoacoustic emission signal through a six-section stimulation signal normal form to obtain a stimulation sound playing sequence diagram in single stimulation frequency otoacoustic emission signal acquisition, and extracting a time domain residual signal; and low-frequency background noise in the time domain residual signals is removed through a zero phase shift high-pass filter with cut-off frequency. And performing stack average processing on the plurality of filtered time-domain signals, and storing the time-domain signals in an odd-order buffer area and an even-order buffer area one by one according to an odd-even order. The method comprises the following steps: performing dimension reduction feature extraction on a single stimulation frequency otoacoustic emission signal through principal component analysis, training a machine learning algorithm based on principal component features, and constructing a hearing loss prediction model; and calling the hearing loss prediction model to compare the feature input with the representation of the single stimulation frequency otoacoustic emission signal without dimension reduction in the original data space, and quantitatively predicting the cochlea hearing loss threshold.

The invention discloses a network construction type energy storage control method and system suitable for black start, and the method comprises the steps: obtaining a three-phase current actual value of a converter side to judge whether an overcurrent fault occurs or not, and switching off a pulse modulation signal of a switching device in a converter when the overcurrent fault is judged to occur; when it is judged that the overcurrent fault does not occur, a three-phase voltage instruction value, output by the power control loop, of the converter is obtained; obtaining a three-phase current actual value of the converter side, enabling the three-phase current actual value to sequentially pass through the virtual resistor and the high-pass filter to obtain a three-phase voltage compensation value, and obtaining a three-phase capacitance current actual value, corresponding to the three-phase voltage compensation value, in the high-pass filter; the difference value between the three-phase voltage instruction value and the three-phase voltage compensation value is used as a compensated three-phase voltage instruction value; and determining a pulse modulation signal of a switching device in the converter according to a difference value between the actual value of the three-phase capacitance current passing through the damping coefficient and the compensated three-phase voltage instruction value. Wave sealing control is applied, fault current limiting is achieved, and the stability of a power grid is improved.

The invention discloses an electroencephalogram signal processing method and system based on motion artifact prediction. The method comprises the following steps: acquiring experimental electroencephalogram data when a testee executes a motion imagination task; discrete wavelet transform is carried out on experimental electroencephalogram data, and signals are decomposed into low-frequency components and high-frequency components through a low-pass filter and a high-pass filter; inputting the low-frequency component into a pre-constructed and trained ARIMA model, and predicting to obtain a linear artifact; inputting the high-frequency component into a pre-constructed and trained XGBoost regression model, and predicting to obtain a nonlinear artifact; combining the linear artifacts and the nonlinear artifacts to generate a complete artifact prediction signal; real electroencephalogram signals are separated through difference value calculation of the experimental electroencephalogram data and the artifact prediction signals. According to the method, the time sequence change of the motion artifacts is predicted by utilizing the ARIMA model, and the nonlinear artifact features are captured in combination with the XGBoost regression model, so that the motion artifacts can be effectively removed, and purer electroencephalogram signals can be recovered.

The invention discloses a composite fault signal separation method based on adaptive spectral kurtosis deconvolution. The method comprises the following steps: S1, carrying out noise reduction processing on an original composite fault signal; s2, separating the composite fault signal after noise reduction through Hilbert envelope demodulation; s3, optimizing a low-pass filter and a high-pass filter through a Bayesian objective function, and constructing a band-pass filter and a band elimination filter; and S4, carrying out iterative filtering on the composite fault signal after noise reduction through a band-pass filter and a band elimination filter, constructing a frequency-bandwidth fast spectral kurtosis graph according to a fast spectral kurtosis deconvolution method, obtaining a center frequency and bandwidth range corresponding to the maximum spectral kurtosis, and separating out the weak fault signal in the step S2. According to the method, a spectral kurtosis graph is constructed by combining a low-pass filter and a high-pass filter through a fast spectral kurtosis deconvolution method to determine the center frequency and the bandwidth range, targeted separation is carried out on composite fault signals, an initial filtering parameter range is provided for Bayesian optimization, and the fault separation efficiency and accuracy are improved.

The invention belongs to the technical field of underwater small target object analysis and recognition methods, and particularly relates to a sound signal feature optimization method for underwater small target object analysis and recognition. Comprising the following steps: 1, acquiring and processing original data; 2, eliminating interference line spectrums, and intercepting and splicing by adopting a time window to obtain a time recombination sound signal; using range transformation to optimize signal amplitude characteristics; processing the sound signal by using an FIR digital high-pass filter; obtaining an optimized signal by using a homomorphic filter; 3, extracting structural features, energy features, frequency features and sound intensity features of the optimized digital signals; step 4, sound signal feature fusion: carrying out underwater target sound signal feature fusion processing based on a canonical correlation analysis method; the invention provides a method for extracting effective sound signal data of an underwater target under the background of optimizing a complex marine environment, enhancing signal effectiveness during long-distance detection, and constructing effective sound signal features capable of being used for classification and recognition of the underwater target at the same time.

The present invention discloses a method and system for industrial defect detection and localization based on frequency domain enhancement, which relates to the fields of computer vision and image processing, can discover abnormal patterns in industrial images from multiple perspectives, and also has a relatively fast inference speed. The method includes: processing an input image through a high-pass filter to obtain a high-frequency image; inputting the original image and the high-frequency image into an improved U-Net network integrated with a dual-domain feature selection module; performing image reconstruction simultaneously in the spatial domain and the frequency domain; calculating an anomaly score and a localization map based on the reconstruction results. By combining spatial domain and frequency domain analysis, the present invention realizes a comprehensive characterization of local pixel changes and global frequency patterns in the image, improving the accuracy of anomaly detection and localization. The method has achieved optimal performance on multiple real industrial scenario datasets. The present invention is applicable to anomaly detection and anomaly area localization of industrial product images.

The invention discloses an industrial defect detection and positioning method and system based on frequency domain enhancement, relates to the field of computer vision and image processing, can discover abnormal modes in an industrial image from a plurality of perspectives, and also has a relatively high reasoning speed. The method comprises the following steps: processing an input image through a high-pass filter to obtain a high-frequency image; inputting the original image and the high-frequency image into an improved U-Net network integrated with a double-domain feature selection module; image reconstruction is carried out in a spatial domain and a frequency domain at the same time; an anomaly score and a localization map are calculated based on the reconstruction result. According to the invention, by combining spatial domain and frequency domain analysis, comprehensive characterization of local pixel change and global frequency mode of the image is realized, and the accuracy of anomaly detection and positioning is improved. The method achieves the optimal performance on a plurality of real industrial scene data sets. The method is suitable for abnormal detection and abnormal area positioning of industrial product images.

The invention provides a false face image detection method based on misleading learning, and the method comprises the steps: S1, constructing a priori knowledge obtaining module, and constructing a basic counterfeit artifact discrimination capability for a counterfeit feature extractor and a detector; s2, establishing a misleading learning knowledge flow and a bias data knowledge flow; s3, introducing a single-channel attention fusion network, and enabling the model to adaptively select required multi-scale counterfeit latent layer features and multi-scale real picture latent layer features; s4, constructing a high-pass filter specially used for misleading learning, and carrying out preprocessing operation on the forged image; s5, misleading learning loss is introduced, and training constraint is carried out on the forged feature extractor; and S6, performing fine adjustment on the forged feature extractor and an adaptive device. According to the method, the model gets rid of feature dependence bias generated by interference of irrelevant semantic features in the picture on the model as far as possible, the method has excellent detection capability for forged pictures of different race statistical tags, and the optimal performance is achieved under intra-domain and cross-domain tests.

A motor control device includes a model following controller to generate a correction torque based on an output from a control target that is a motor, and correct an input to the control target with the correction torque. A model following controller includes a high-pass filter with a first cutoff frequency and a low-pass filter with a second cutoff frequency larger than the first cutoff frequency, and is configured or programmed so that a transfer function of a control target is constrained to a nominal model in a frequency band in which a gain in a gain characteristic of Q(s)·HPF(s) is 1 where Q(s) is a transfer function of the low-pass filter and HPF(s) is a transfer function of the high-pass filter.

A band-pass filter includes a first port, a second port, first to third high-pass filters provided between the first port and the second port in this order from a first-port side in a circuit configuration, and a low-pass filter provided between the second high-pass filter and the third high-pass filter in the circuit configuration. Each of the first to third high-pass filters forms an attenuation pole on a low-pass side of the passband. A frequency of the attenuation pole formed by the second high-pass filter is higher than a frequency of the attenuation pole formed by each of the first and third high-pass filters.

The invention relates to the technical field of hybrid energy storage control strategies, and discloses a hybrid energy storage progressive model prediction control method based on optimal duty ratio tracking. The method comprises the following steps: setting a front-end MPC and a rear-end MPC which are used for controlling the on-off of a switching tube in a system, selecting an optimal duty ratio output corresponding to the minimum cost function of the front-end MPC, driving the on-off of the corresponding switching tube to stabilize the bus voltage, calculating the real-time optimal reference power of hybrid energy storage at the next moment, and taking the real-time optimal reference power as the real-time optimal reference value of the rear-end MPC after passing through a high-pass filter; and selecting the corresponding optimal switching state output when the cost function of the rear-end MPC is minimum, and driving a corresponding switching tube to be switched on and switched off, so that the output power of the super capacitor tracks a real-time optimal reference value given by the front-end MPC in real time, the power fluctuation is stabilized, and the bus voltage is further stabilized. According to the invention, the fluctuation of the bus voltage is smaller under the fluctuation of the load power; and optimal reference power transmission under model prediction control is considered, so that the control performance is optimized.

The invention provides a multi-sensor fusion downhole drilling tool rotating speed control method and application. The rotating speed control method comprises the steps that rotating speed measurement is conducted, specifically, the rotating speed of an internal control system is obtained through a gyroscope and a vibration sensor, and the rotating speed of an external drill collar is obtained through a magnetoresistive sensor and the vibration sensor; rotating speed control: when the internal control system is static in space, the gyroscope acquires rotating speed data of the internal system, and the vibration sensor acquires vibration data; processing the vibration data by using a Butterworth high-pass filter, extracting rotation speed fluctuation, and performing torque compensation on internal system rotation speed data acquired by the gyroscope according to the rotation speed fluctuation to obtain a real-time rotation speed of an internal control system; when the internal control system rotates along with a certain rotating speed difference or the internal control system is switched between a static mode and a rotating along mode to do variable motion, the relative rotating speed of the real-time rotating speed of the internal control system and the real-time rotating speed of the external drill collar is measured, the rotating speed of the internal control system is adjusted through a gyroscope, and the relative rotating speed is measured multiple times till the expected effect is achieved.

An apparatus and method are provided to correct for time-walk errors during photon detections (e.g., detecting gamma rays). A time-walk correction is determined using measurements of energy (or charge) that apply different time windows, enabling corrections accounting for variations in the ratio between fast and slow components in the detected pulse. For example, one time window can be used to integrate the leading end of the pulse, thereby predominantly measuring the fast component, while a second window is used to integrate a trailing end of the pulse to predominantly measure the slow component. Alternatively or additionally, low-pass and high-pass filters may select the slow and fast components, respectively. The time-walk correction is a function of multiple measurements representing different components (e.g., fast and slow) of the pulse shape.

The invention belongs to the technical field of magnetic particle imaging, particularly relates to a time sequence magnetic nanoparticle imaging device and method for detecting nerve response activity, and aims to solve the problems that the sensitivity of magnetic particle signal detection is not high, a large coil assembly is needed for achieving high magnetic field intensity, the calculation amount is large, and the calculation mode is complex. According to the device, a signal generator outputs a voltage signal, amplifies the voltage signal and then accesses a selection coil and a driving coil; the two selection coils are arranged in a Maxwell configuration and have the same axis; the driving coils are arranged at intervals of 90 degrees from top to bottom, from left to right and from front to back by taking the FFR as the center; the excitation coil, the receiving coil and the selection coil are coaxial; and the high-pass filter filters the signal received by the receiving coil and imports the signal into a computer through a signal acquisition card for time sequence fMPI image sequence reconstruction. According to the invention, the magnetic particle signal detection sensitivity is improved, the volume of the coil assembly is reduced, the calculation complexity and the calculation amount are simplified, and the magnetic particle imaging robustness is improved.

The invention provides a brain image denoising method based on a U-shaped dynamic convolution multi-scale multi-branch network. The brain image denoising method comprises the steps that brain noise images to be denoised are input into three branch networks formed by U-netAM, DSHFN and MSDSRN in parallel; in the U-netAM branch, multi-level features are extracted through an encoder in sequence, after weighting is conducted through a channel and a space attention mechanism, the spatial resolution is recovered through a decoder, and a first feature map is obtained; in the DSHFN branch, the dynamic convolution kernel generates a corresponding convolution kernel in real time according to input image features, the image is decomposed into a low-frequency part and a high-frequency part, and the low-frequency part and the high-frequency part are subjected to weighted fusion after being processed by a low-pass filter and a high-pass filter respectively to obtain a second feature map; in the MSDSRN branch, adopting multi-scale depth separable convolution to extract multi-scale features in parallel, and obtaining a third feature map through residual connection and fusion; inputting the three feature maps into an FPB block for fusion to obtain a noise feature map; and performing pixel-by-pixel subtraction on the original brain noise image and the noise feature map, and outputting a denoised brain image.

The invention discloses a power distribution control method and device for a photovoltaic hybrid energy storage direct current microgrid based on fuzzy second-order high-pass filtering, and the method comprises the steps: researching the topological structure and working principle of the photovoltaic hybrid energy storage direct current microgrid and the energy management of the microgrid, and obtaining a power balance relation of the direct current microgrid; a comprehensive operation control strategy of the micro-grid is established, and it is determined that a photovoltaic power generation unit adopts maximum power point tracking control of fuzzy control, a grid-connected inverter adopts double closed-loop control of a voltage outer loop and a current inner loop, and a hybrid energy storage unit adopts fuzzy second-order high-pass filtering algorithm control; frequency division distribution and stability of a traditional second-order high-pass filter are studied, so that the second-order high-pass filter based on fuzzy logic is further studied, the SOC of the super capacitor is determined as a control index, and a fuzzy rule of a filtering time constant is adaptively adjusted; the established fuzzy logic variable time constant second-order high-pass filtering control simulates and compares the hybrid energy storage system power, the DC bus voltage and the super capacitor SOC under the variable illumination and load conditions with the fixed constant second-order high-pass filtering control, and compares the change curves of the super capacitor SOC of two strategies under the condition of changing the initial SOC value of the super capacitor. Three-phase current and current total harmonic distortion of the two strategies are compared, and it is verified that the efficiency of a photovoltaic power generation system is improved under the strategies, the SOC of a super capacitor changes within a reasonable range, a micro-grid can stably operate in a grid-connected mode, and grid-connected current harmonic distortion is effectively reduced.

A motor control device includes a torque controller to operate based on a steering torque and to give an input to a control target that is a motor, and a model following controller to generate a first correction torque based on an output from the control target. A model following controller includes a high-pass filter to remove a low frequency component from a first correction torque, a friction compensation calculator that is coupled in parallel to the high-pass filter to apply friction compensation to the first correction torque to calculate an estimated value of a mechanical friction torque, and an adder to add the estimated value of the friction torque to the first correction torque from which the low frequency component is removed by the high-pass filter to generate a second correction torque and feed back the second correction torque to an input to the control target.

The invention, which belongs to the technical field of cable fault detection, discloses a detection apparatus and method for a cable fracture position in an expressway, the detection apparatus comprises an audio oscillator, a buffer, a high-pass filter, an output amplifier, a detector, an earphone, a data processing module and a user interface, the audio oscillator, the buffer, the high-pass filter and the output amplifier are sequentially connected, the input ends of the detector and the earphone are respectively connected with the output amplifier, the output ends of the detector and the earphone are both connected with the data processing module, and the data processing module is connected with the user interface. According to the device for detecting the fracture position of the cable in the expressway, a detection signal is applied to the exterior of the cable, so that damage to an insulating layer of the cable by a traditional method is avoided, and non-contact detection is realized.

The invention discloses a semi-active suspension control strategy based on IIR (Infinite Impulse Response) filter frequency division, which is characterized in that an acceleration sensor is used as input, a low-pass IIR filter and a high-pass IIR filter are respectively used for processing the acceleration of a cab, and appropriate damping is output according to a result so as to suppress the resonance phenomenon of a vehicle body during low-frequency vibration; and the vibration isolation coefficient during high-frequency vibration is improved. According to the method, the number of required sensors is small, the complexity is low, the computing power requirement for hardware is small, the cost of the semi-active suspension can be effectively reduced, and the method has a certain engineering practical application value and is high in generalizability. Test results show that compared with passive suspension, the control strategy can effectively reduce vibration of a vehicle cab in the x direction and the z direction, so that the comfort index of the long-distance logistics vehicle is improved, x-direction optimization is 21.3% at most, and z-direction optimization is 11.7% at most.

A system and method for monitoring signal quality metrics coupled with closed-loop control improves rectifier signal quality and stability. The closed-loop control passes the metric through a high-pass filter and captures error values. This signal is then passed to a controller to adjust rectifier settings. The measured signal, where signal quality is derived could be VRECT, FCLK, network coil measurements, is used for ASK demodulation, or the like. The controller identifies noise levels and noise types in real-time, and sets parameters of the rectifier to preserve system stability. The controller may set baud rates and preamble thresholds in a wireless power transfer system in response to identified noise levels and types.

An analog-to-digital converter circuit module utilizing dither to reduce multiplicative noise. A dither generation circuit generates a noise-shaped analog dither signal having lower amplitudes at frequencies below a cutoff frequency than at frequencies above the cutoff frequency. The noise-shaped analog dither signal is added to the input analog signal to be converted and the summed signal applied to an analog-to-digital converter The dither generation circuit may be implemented as an analog dither generator followed by an analog high-pass filter. The dither generation circuit may alternatively be implemented digitally, for example with a digital noise-shaping filter applying a high-pass digital filter to a pseudo-random binary sequence. The digital dither generation circuit may alternatively be implemented by one or more 1-bit sigma-delta modulators, each generating a bit of a digital dither sequence that is converted to analog.

Embodiments of the invention include a plasma system. The plasma system includes a plasma chamber; an RF driver configured to drive bursts into the plasma chamber with an RF frequency; a nanosecond pulser configured to drive pulses into the plasma chamber with a pulse repetition frequency, the pulse repetition frequency being less than the RF frequency; a high pass filter disposed between the RF driver and the plasma chamber; and a low pass filter disposed between the nanosecond pulser and the plasma chamber.

The invention discloses a portable electroencephalogram signal acquisition system and method. The portable electroencephalogram signal acquisition system comprises an electroencephalogram acquisition electrode, a filtering and amplifying circuit, an AD conversion circuit, a main control circuit and a communication module, wherein the filtering and amplifying circuit comprises a high-pass filter circuit, an amplifying circuit and a low-pass filter circuit; the electroencephalogram collecting electrode is used for collecting electroencephalogram signals and connected with the input end of the high-pass filter circuit, the output end of the high-pass filter circuit is connected with the input end of the amplifying circuit, the output end of the amplifying circuit is connected with the input end of the low-pass filter circuit, and the output end of the low-pass filter circuit is connected with the main control circuit through the AD conversion circuit. The high-pass filter circuit is used for filtering low-frequency noise in the electroencephalogram signals, the low-pass filter circuit is used for filtering high-frequency interference signals in the electroencephalogram signals, the main control circuit is further connected with the communication module, limitation of traditional equipment is broken through, and stability of data transmission is ensured.

An audio amplifier includes a loop filter, at least one high pass filter (HPF) circuit, a pulse width modulation (PWM) generator, and a power stage. The loop filter is arranged to receive an audio signal and a feedback signal, and includes a first amplifier and a second amplifier, wherein the first amplifier has a first output node, and is arranged to process the audio signal and the feedback signal; the second amplifier has a first input node, and is arranged to receive a first amplifier input and a second amplifier input; and the first amplifier input is obtained from a signal path coupled between the first output node and the first input node. The at least one HPF circuit is coupled between the first amplifier and the second amplifier, and is arranged generate and output the second amplifier input according to an amplifier output of the first amplifier.

The invention discloses a novel chopping correlation double-sampling stable multi-path amplifying circuit and method, and relates to integrated circuit design. A Miller compensation capacitor in a chopping stable multi-path CSMP amplification circuit architecture is utilized to design a chopping correlation double-sampling circuit, and compared with a traditional correlation double-sampling circuit, a group of sampling capacitors and sampling switches are reduced. Large capacitance and large resistance required by a traditional high-pass filter circuit are eliminated, and the layout area and the current required for driving a high-pass filter capacitor are reduced; and thermal noise caused by large resistance in the passive high-pass filter is reduced, and the input equivalent noise density is improved. Through an offset calibration technology, the stability of the CSMP architecture is ensured, and the offset voltage is reduced at the same time; output ripples are suppressed by using the high-pass performance of the novel chopping correlation double-sampling circuit, 1 / f noise is reduced, and input equivalent noise density is reduced. The advantages of the chopping correlation double sampling technology and the stable multi-path amplification circuit are combined, and the advantages of low offset, low output ripple and low input equivalent noise density are achieved.

The embodiment of the invention provides a ripple signal processing circuit, a high-voltage power supply circuit and high-voltage power supply equipment, the ripple signal processing circuit comprises a high-pass filter and a voltage follower circuit, the high-pass filter is used for obtaining a voltage input signal and outputting a ripple signal in the voltage input signal, and the voltage follower circuit is used for outputting the ripple signal in the voltage input signal. And the impedance converter is used for receiving the ripple signal, performing impedance conversion and outputting an output signal to an oscilloscope. In the technical scheme, the equivalent resistance of the high-pass filter is equal to the resistance after the internal resistance of the high-pass filter and the resistance of the voltage follower circuit are connected in parallel. Therefore, the equivalent resistance of the high-pass filter is not affected by the internal resistance of the oscilloscope. When the capacitance of the high-pass filter is fixed, the larger the resistance value of the internal resistor of the high-pass filter is, the lower the cut-off frequency of the high-pass filter is, and the frequency of the ripple signal detected by the oscilloscope is lower.

The embodiment of the invention provides a hierarchical control method, system and device for battery energy management, and belongs to the technical field of discharge control of batteries. The control method comprises the following steps: acquiring total required power; separating high-frequency power from the total demand power by adopting a second-order high-pass filter; subtracting the total required power from the high-frequency power to obtain low-frequency power; inputting the high-frequency power into a super capacitor to obtain super capacitor power; subtracting the high-frequency power from the power of the super capacitor; adding the difference value of the high-frequency power and the power of the super capacitor and the low-frequency power to obtain the total power required by the battery and the lithium battery; and determining optimal battery power and lithium battery power by adopting a preset optimization algorithm according to the total required power of the battery and the lithium battery by taking the minimum equivalent hydrogen consumption as an optimization target and taking the start-stop times, the power change rate and the maximum power which influence the performance degradation of the battery as constraint conditions.