17 results about "Time domain model" patented technology

The application discloses a hybrid system network converter long-time domain prediction control and non-disturbance switching method, and belongs to the technical field of power system control. In view of the problems of poor dynamic performance of a hybrid system of a network construction / following network converter under high proportion of new energy grid connection and easy impact of mode switching, the method is as follows: a long-time domain model is constructed to predict current control, a traditional PI current inner ring is replaced, a dq coordinate system is discretized to model, double-step length prediction is compensated to delay, a Lagrange extrapolation is used to update a reference current, current tracking accuracy and harmonic suppression capability are improved; a non-disturbance switching strategy is designed, an alpha-beta coordinate system and a current control ring are unified, a switching angle is locked and an initial value of an integrator is synchronized, a reference voltage is dynamically adjusted to guarantee variable continuity; the two strategies are integrated into a hybrid framework, stable operation and smooth switching under strong / weak power grid and transition working conditions are realized. The application reduces grid-connected current total harmonic distortion rate to below 0.85%, has no voltage and current impact in switching, and has the advantages of enhancing power system stability and flexibility.

The application discloses a CLLC resonant converter soft-start method, device, equipment and medium. The method comprises the following steps: a time domain model of a converter under PWM control is established, and a nonlinear mapping relationship between a voltage gain and a duty cycle is obtained by solving; the gain is set to increase linearly with time, and a nonlinear curve of the duty cycle changing with time is back calculated; finally, two-stage control is executed: in the first stage, the duty cycle is increased to a set maximum value according to the nonlinear curve every cycle under fixed high frequency, so that the output voltage linearly rises; in the second stage, the duty cycle remains unchanged, and the switching frequency is gradually reduced to the resonant frequency. The application can completely eliminate the current peak at the starting moment, shorten the forward starting time to one-tenth of the traditional time, realize smooth establishment of the output voltage without overshoot, and effectively reduce the high-frequency requirement of the device and the system cost.

The present application relates to electric bus charging joint scheduling technical field, provide electric bus fixed and dynamic wireless charging joint scheduling method and system. Electric bus fixed and dynamic wireless charging joint scheduling method includes that fixed and dynamic wireless charging coordination problem is modeled as limited time domain constraint Markov decision process, and then the power of fixed and dynamic wireless charging is determined as charging scheduling strategy based on system state, and the optimization objective function is constructed as minimizing cumulative expected energy cost within the set operation period; the optimization objective function is solved by using the rolling time domain model predictive control method, and the terminal SOC shortage cost is decomposed into the expansion and contraction of the stage cost by using the convex potential function, while keeping the optimal charging scheduling strategy, the end of the day requirement is internalized in the rolling time domain of the rolling time domain model predictive control method.

A method for analyzing the dynamic characteristics of an air spring is disclosed, establishing time-domain and frequency-domain models of its dynamic characteristics. The method includes: identifying parameters of the effective area and volume of the air spring through experimental methods; fitting the friction force using a friction model; establishing a differential equation for the internal air pressure change of the air spring and identifying the heat transfer coefficient through experimental methods; establishing a time-domain model of the air spring's dynamic characteristics; linearizing the time-domain model to establish a complex dynamic stiffness model of the air spring; and establishing frequency-domain models of the air spring's dynamic stiffness and hysteresis angle based on the complex dynamic stiffness. This invention offers the following advantages: it can predict the force-displacement relationship of an air spring under excitation at any frequency; it provides a method for identifying the heat transfer coefficient; and it can predict the dynamic stiffness and hysteresis angle of the air spring under different excitation amplitudes and frequencies.

This invention relates to the field of energy-saving planning technology, and more particularly to an energy-saving planning method for multi-segment driving of electric vehicles based on signal-sequential logic. The method includes the following steps: acquiring global topology information and dynamic traffic information of the target driving path; constructing a multi-layer weighted spatiotemporal graph model based on the global topology information and dynamic traffic information; collecting corresponding state information in real time, and constructing a fused mechanical-electrical-thermal coupled dynamics vehicle prediction model based on the multi-layer weighted spatiotemporal graph model and the real-time collected state information to predict the future vehicle state trajectory under different driving strategies; formalizing it into a temporal logic proposition within the signal-sequential logic framework and embedding it into a finite-time domain model predictive control problem; and generating a corresponding collaborative optimization sequence by solving the finite-time domain model predictive control problem with embedded temporal logic constraints, thereby achieving integrated energy-saving planning for driving, energy, and heat. This invention can significantly alleviate range anxiety in electric vehicles.

The invention relates to the technical field of process safety operation, in particular to a process continuous operation method and system, electronic equipment, a storage medium and a program product, and the method comprises the steps: constructing a time domain model according to a dynamic mechanism of a process system; converting the time domain model into a complex frequency domain model through Laplace transformation; solving a complex frequency domain optimal continuous operation variable based on the complex frequency domain model, and converting the complex frequency domain optimal continuous operation variable into a time domain optimal continuous operation variable through inverse Laplace transformation; and performing continuous operation based on the time domain optimal continuous operation variable. According to the process continuous operation method, an analytical method based on a complex frequency domain is provided, continuous working condition switching of a complex chemical system is achieved, compared with a subsection control strategy, the continuous control strategy can describe the real situation as much as possible, feature details of operation variables are clearly presented, higher information density is achieved, and the method is suitable for large-scale popularization and application. And therefore, the safety and the stability of the production process can be improved.

The application provides a state space-based multi-line DC power flow controller modeling and control parameter optimization method, the instability of the DC network ring network system caused by the addition of the DC power flow control is made up by adding the matrix E containing PI control, and the influence of the phase margin and the dynamic characteristic is considered, the game optimization of the control parameters in the dynamic time domain model is carried out based on the eigenvalue, and the application has high universality and strong portability, and has high guiding significance for improving the control performance and optimization ability of the line-to-line power flow controller. The application models the multi-line DC power flow controller, breaks through the barrier of the scale expansion of the DC power flow controller, has the advantages of simple structure, high universality, strong applicability and the like, and provides a model basis for the subsequent research of the DC power flow controller.

This invention provides a real-time speed control method and system for injection in a die-casting machine. The system includes a human-machine interface, an Ethernet communication interface, an MCU controller, an FPGA high-speed execution unit, a sensor group, and an execution mechanism. The FPGA performs data acquisition, pressure / flow inner loop, amplitude limiting and slope limiting, and parallel drive of valves and pumps. The MCU obtains speed feedback based on the injection plunger position, servo pump speed, and injection chamber pressure change rate according to the outer loop scheduling cycle, and performs stage identification, online parameter identification, candidate model selection, expansion state observer disturbance compensation, and short-time domain model predictive control of the switching window. This method reduces stage switching impact and pressure overshoot by identifying the hydraulic execution channel pilot in the low-speed safety detection interval before injection, performing multi-anchor point curve superposition calibration, stage authorization token interlocking, and multi-source residual fault reconstruction, thereby improving injection accuracy, batch consistency, and operational safety.

The application relates to an adaptive online fault diagnosis method and system, and belongs to the field of fault diagnosis. The method comprises the following steps: constructing a time domain model and a frequency domain model; dividing a time domain vibration signal into a plurality of time sequence segments, and performing real number discrete Fourier transform on each segment to obtain a frequency domain signal; training the model by using the time domain signal and the frequency domain signal respectively to obtain a time domain source model and a frequency domain source model; initializing a target domain time domain model and a target domain frequency domain model based on source model parameters; replacing a batch normalization layer in the target domain model with an instance-aware batch renormalization layer; performing Fourier transform on an online small batch signal, and inputting the signal into the target domain model to calculate uncertainty loss and consistency loss; and traversing all small batch data to obtain a fault diagnosis result. The application solves the problem that under the conditions of online and passive data, the statistical estimation capability is weak due to the fact that time domain and frequency domain information cannot be used simultaneously.

The application discloses a model parameter identification method suitable for fuzzy PID control, and comprises the following steps: step (1), a first-order inertia plus pure lag FOPDT model suitable for adapting dynamic characteristics of a temperature control system is established; step (2), inverse Laplace transformation is carried out on a transfer function of the FOPDT model, a complex frequency domain model is converted into a time domain model, and a noise term e(t) is introduced in combination with interference factors existing in actual operation of the temperature control system to modify the time domain model. The application can realize accurate identification of dynamic characteristics of a controlled object in the temperature control system, provide a reliable model basis for adaptive setting of fuzzy PID control parameters, effectively solve the problem of poor parameter adaptability in traditional temperature control, guarantee high precision and long-term stability of the temperature control process, and can be widely applied to fields, such as industrial kilns, constant-temperature laboratories and semiconductor manufacturing, which have strict requirements on temperature control precision.

This invention belongs to the field of new energy power generation grid connection technology, and discloses a modeling method, system, equipment, and medium for grid-side converter fault ride-through control structure. It addresses the problems of difficult modeling, high cost, poor extrapolation, and lack of versatility in existing technologies due to reliance on manufacturer-internal logic or massive experimental data. The method acquires disturbance input and current output data under finite operating conditions, constructs an up-dimensional mapping function to map the input to a high-dimensional feature space, establishes a global linear mapping model based on ridge regression to solve the Koopman operator, predicts active and reactive current reference components, and finally generates the current transient response curve during the fault period using the inner-loop time-domain model of the input current. This invention requires only a small number of samples to achieve high-precision modeling and prediction, has good extrapolation and versatility, and can be adapted to various fault ride-through strategies.

This application provides a method for predicting quality indicators in complex industrial processes, comprising: collecting time series data of multidimensional industrial process variables and constructing a training set; constructing a quality indicator prediction model, including: constructing feature extraction structures based on time-domain and frequency-domain models in parallel, extracting time-domain and frequency-domain features of the multidimensional industrial process variable time series through the time-domain and frequency-domain models respectively; fusing the time-domain and frequency-domain features through an attention mechanism to obtain time-frequency fusion features; introducing a slow-varying feature extraction mechanism to constrain the time-frequency fusion features and extracting slow-varying driving features reflecting the intrinsic mechanism of complex industrial processes; fusing the time-frequency fusion features with the slow-varying driving features; training the quality indicator prediction model using the training set; and using the trained quality indicator prediction model to predict key quality indicators of complex industrial processes online. This application effectively solves the problem of the difficulty in timely acquisition of key quality indicators in complex industrial processes.

This invention relates to shortwave communication technology, and particularly to a shortwave MIMO channel modeling method based on multi-domain coordination of time-space-frequency-polarization-angle. The method includes: constructing a nonlinear array of transceiver antennas; determining the geometric relationships of element spacing, element velocity, distance from the reflector cluster to the antenna, and reflector cluster velocity based on three-dimensional vectors; establishing a path transmission delay characterization mechanism jointly determined by propagation distance, the number of inseparable multipath paths, and time-difference statistical characteristics; decomposing the distance from the element to the reflector cluster into time-space stationary and non-stationary terms; establishing a polarization matrix and performing amplitude-phase weighting on multipath components with different arrival and departure angles; obtaining the existence and disappearance states of the path over time based on the reflector cluster probability model combined with Markov processes; incorporating the influence of antenna polarization on channel amplitude into the channel expression; and generating impulse response and corresponding scattering functions using the obtained angular power spectrum, delay domain model, and time-varying path state model. This invention improves the polarization adaptability of large-scale arrays to actual arrays.

The application relates to the technical field of wireless power transmission, and particularly discloses a wireless power transmission system with a position detection function. In order to meet the alignment accuracy specified in the standard while reducing the complexity and cost of position detection, the secondary side compensation inductance and the receiving coil are integrated in the same magnetic core, so that the system power density and compactness are improved; by utilizing the monotonic change of mutual inductance between the integrated inductance and the transmitting coil when the position is offset, only the phase difference between the inverter output current and the driving voltage needs to be detected on the primary side, the offset position can be real-time backstepping, no additional sensors or switching devices are needed, and the hardware cost is significantly reduced. Meanwhile, by establishing an accurate time domain model analysis, the detection variable (the phase difference between the inverter output current and the driving voltage) and the phase difference acquisition approach are determined, and the phase difference detection accuracy is improved. The system meets the alignment accuracy requirement of wireless charging, is suitable for scenes such as electric vehicles and industrial robots, and realizes the low-cost and high-reliable alignment guiding function.

The application discloses a heavy-load AGV hydraulic suspension posture keeping method, and belongs to the technical field of heavy-load AGV control. The method obtains a vehicle-road combined state vector through a sliding mode-extended Kalman filter, obtains a vehicle linearized dynamic matrix and a covariance thereof through a gated recurrent unit network, and on the basis, uses a variable prediction time domain model prediction controller to output a target cylinder displacement instruction and a pressure instruction, and corrects the instruction in real time, so as to realize dynamic level control of a vehicle platform. The method forms a perception, decision and execution closed-loop adaptive link through a four-source coupled road and mass center estimation link, a double-layer decision architecture composed of a gated recurrent network and a model prediction control, and a hydraulic network tension compensation mechanism based on a graph convolution network, can synchronously update a road prior, a load distribution and a multi-cylinder pressure instruction in a millisecond time scale, and thus significantly improves dynamic level and energy utilization.