167 results about "Hardware-in-the-loop simulation" patented technology

The invention discloses an aerospace equipment data-real fusion performance test method and device based on reinforcement learning, and the device comprises a digital twin model building module which is used for building an aerospace equipment high-fidelity mechanism model fusing multi-physical field features, a lightweight digital twinborn body adaptive to reinforcement learning training is generated through a model order reduction technology; the digital twinborn model correction module is used for carrying out consistency calibration of multi-dimensional features and key physical parameter correction on the reduced-order model based on object reference data; the performance test module based on reinforcement learning actively explores a coupling scene of an extreme working condition and multiple faults in an interaction environment by constructing an attacker agent, and autonomously explores a performance boundary and a limit envelope of equipment; and the number-real fusion verification module is used for carrying out a hardware-in-the-loop point compensation test by taking the performance limit obtained by the digital test as guidance so as to assist in decision making and optimization of a test scheme. According to the method, the coverage, the safety and the test efficiency of the limit performance test of the aerospace equipment are improved.

The invention discloses a hardware-in-the-loop test method and device and electronic equipment, relates to the technical field of automotive electronics, and adopts a simulated annealing algorithm in an optimization stage, adjusts parameters according to characteristics of an electronic stability control system, optimizes data distribution, and improves test data quality and fault detection capability. In the verification stage, the generated test data is subjected to actual operation test, the data problem is fed back by comparing actual output with an expected result, and the optimized test data which does not pass verification is sent to the target hardware-in-loop test model for optimization adjustment, so that a closed-loop optimization verification process is formed. The iterative closed-loop process comprehensively covers all possible working conditions and fault modes, key test points are prevented from being omitted, the reliability of the electronic stability control system is enhanced, the accuracy, effectiveness, comprehensiveness and sufficiency of hardware-in-the-loop test of the electronic stability control system are ensured, and the reliability of the electronic stability control system is improved. And the limitation of hardware-in-the-loop test of the electronic stability control system is reduced.

The invention discloses a real-time SLMP fuel cell hybrid electric vehicle energy management method. The method comprises the following steps: firstly, collecting vehicle operation data in real time, constructing an operation state vector containing kinetic parameters, and initializing a state transition matrix as agent action input; on the basis, the speed and the acceleration are predicted through a self-learning Markov predictor, and dynamic self-adaptive power distribution of the fuel cell and the power cell is achieved in combination with a multi-objective optimization function and power distribution constraints. The method passes hardware-in-the-loop (HIL) verification, aims at reducing hydrogen consumption and improving efficiency, and exits if two times of circulation are not passed. Compared with a traditional method based on rules or static optimization, the method innovatively embeds a self-learning mechanism, has the advantages of being high in adaptability, high in prediction precision and good in generalization performance, and is suitable for energy management optimization under complex working conditions.

A hardware-in-the-loop test method and system for a protection device. The method comprises: constructing a simulation scenario in a hardware-in-the-loop simulation test system; on the basis of the mounting position of a protection device (4) to be verified in the simulation scenario, determining the minimum sampling signals required for said protection device (4) to work normally, and establishing a current transformer model capable of restoring a transient saturation scenario; performing a power-on operation on said protection device (4), and enabling the hardware-in-the-loop simulation test system to output an electrical signal; and after a correct sampling reading is acquired on said protection device (4), simulating a fault scenario in the simulation scenario, and on the basis of a current signal having transient saturation characteristics calculated by a model and a logic determination of the protection device, determining whether an action result of the fault scenario satisfies a setting value and an action logic. The present hardware-in-the-loop test method for a protection device restores a true current in a non-ideal fault condition, thereby deeply testing the working characteristics of a relay protection device in a power station.

The invention relates to the technical field of new energy, and discloses an optimization method for an intelligent yaw system of a wind generating set, and the method comprises the steps: building the intelligent yaw system, enabling the system to be internally provided with seven modules, and enabling a multi-sensor data collection module to collect wind direction, wind speed and yaw angle data in real time, the data fusion module performs Kalman filtering fusion processing to obtain a high-confidence state estimation value, the intelligent decision output module generates an optimal yaw control instruction by adopting a multi-mode control strategy and a parameter self-adaptive mechanism based on fused data, an execution mechanism is driven to realize accurate wind alignment, and the system integrated hardware-in-the-loop test module is used for realizing accurate wind alignment. Omnibearing verification can be carried out before deployment, after actual operation, operation indexes are continuously monitored through the performance evaluation module, control parameters and fusion algorithm parameters are adjusted online through the optimization module on the basis of methods such as machine learning, closed-loop optimization is formed, finally, yaw precision, response speed and system stability are remarkably improved, and maintenance cost is reduced.

The invention discloses an input-output method and system realized based on a calculation engine in the coal chemical industry, and relates to the technical field of coal chemical industry, and the method comprises the steps: building a molecular model based on a reaction network of a coal molecular structure, and updating the parameters of the molecular model in real time through extended Kalman filtering; constructing a data fusion layer through a hybrid modeling technology, and constructing a coal chemical industry residual learning architecture by using a mechanism model and a neural network series structure; evaluating a data-driven model prediction confidence interval according to a Monte Carlo method; a digital twin verification platform is constructed based on hardware-in-the-loop test, and a data-driven adaptive iteration mechanism is constructed through an online and offline collaborative updating mechanism. The method has the beneficial effects that the medium component fluctuation is accurately captured, the output accuracy is improved, reliable evaluation dependence is provided, and the real-time response force and long-term stability of the system in a complex environment are improved.

The invention provides a desktop-level hardware-in-the-loop test system building method, device and equipment, and relates to the technical field of hardware-in-the-loop simulation, and the method comprises the steps: configuring a vehicle network simulation and vehicle dynamics model in an upper computer with a CAN development environment and vehicle dynamics simulation software, a real-time data channel between the two is established through a full duplex transmission protocol; a driver instruction is generated through the driving control panel, and a vehicle state signal is generated through vehicle dynamics software; the wheel speed in the vehicle state signal is converted into a physical excitation signal, and a wheel cylinder pressure signal returned by the controller is collected; the pressure signal is fed back to the vehicle dynamics model to form a closed loop, a test scene is executed, and the desktop-level hardware-in-loop test of the brake controller is completed. By using vehicle dynamics simulation software, the test confidence coefficient is improved; data exchange is carried out by utilizing an FDX protocol of a CAN development environment, and complexity and potential risks of self-development of a communication interface are avoided.

The invention discloses an automatic test system for detecting an IO port on an MCU controller, and particularly relates to the technical field of automatic test and hardware-in-the-loop verification, the system takes a TSMaster as an upper computer, a programmable power supply, a digital multimeter and a controllable relay matrix are combined, and input injection, output measurement and controlled power supply disturbance are realized through a CAN / Ethernet / SCPI. The system comprises an input injection and channel switching module, an output drive and high-resistance isolation module, a power supply disturbance and alarm verification module, a unified acquisition and self-calibration compensation module, a criterion evaluation / report module, a regression module and the like, completes alignment and online small signal calibration and crosstalk compensation under a unified time base, constructs a minimum evidence unit, and implements interval criterion and time sequence robustness evaluation. And outputting an auditing report and triggering regression scheduling to realize high coverage of IO port functions and boundary working conditions and repeatable verification.

The invention provides a hardware-in-the-loop test device. The hardware-in-the-loop test device comprises a simulation model verification system used for obtaining real-time data of input and output of an IO terminal of a DCS system in various operation states; the real-time data is transmitted to the fault state detection system; the fault state detection system is used for converting real-time data into a control signal and transmitting the control signal to the simulation data signal IO system; the simulation data signal IO system is used for converting the control signal into an electric signal; the electric signal is transmitted to a fault signal injection system; and the fault signal injection system is used for superposing the fault signal on the electric signal to obtain various types of faults, and transmitting the electric signal superposed with the fault signal to the DCS. According to the invention, the hardware-in-the-loop test device simulates each external signal fault of the DCS system, and injects the fault signal into the DCS system, thereby verifying and improving the robustness of the DCS system and a simulation model, and meeting the reliability test of the DCS system under an extreme working condition.

The invention discloses a reinforcement learning-power hardware-in-the-loop training system and method for a power converter, and belongs to the technical field of power electronic control and artificial intelligence crossing. The system comprises a real-time digital simulator, a power amplifier, a controlled power converter and an AI accelerator. The method comprises the steps of S1, system initialization and environment configuration; s2, performing safe online training; and S3, strategy convergence and solidification. Through the power hardware-in-the-loop architecture, the risk of reinforcement learning exploration is completely avoided, and hardware damage caused by overvoltage and overcurrent is fundamentally eradicated in combination with a real-time hardware protection strategy. According to the method, the real object power converter controller is incorporated into a training closed loop, so that an intelligent agent strategy directly learns and adapts to the nonlinear dynamic state of real hardware, the gap from simulation to reality is thoroughly filled up, and it is ensured that a training result can be directly applied to an actual system. According to the invention, a full-real-time training system is constructed, and synchronous concurrent processing of data acquisition, strategy execution and model updating is realized.

The invention belongs to the technical field of power systems, and particularly discloses a controller hardware-in-the-loop wind turbine generator transmission chain test platform simulation method, which comprises the following steps: designing parameters of a wind turbine generator, and constructing a wind turbine generator simulation model; establishing a wind field model, and embedding the wind field model into the wind turbine generator simulation model; constructing a transmission chain model and performing data connection with the wind turbine generator simulation model; constructing a control system comprising a main controller model and a subsystem control system, and establishing a control instruction channel and a feedback signal channel for the subsystem control system and the transmission chain model; deploying a control system in a rapid control prototype, and connecting the control system with the simulation platform through a physical interface; transmission chain operation data are collected in the simulation process, and the control strategy of the experimental platform and the transmission chain performance are evaluated. The hardware-in-the-loop simulation technology is utilized, closed-loop operation between the controller entity and the virtual model is achieved, and the authenticity of transmission chain experiment platform control strategy verification and the flexibility of experiment platform debugging are effectively improved.

The invention relates to the technical field of curved screen testing, and discloses a hardware-in-the-loop self-adaptive testing method and system for a curved screen and a storage medium. The method comprises the steps that the model of the curved screen is obtained, bending information and a two-dimensional coordinate system are extracted from a hardware model library, and a multi-axis testing arm three-axis basic assembly is initialized; starting a corresponding bending shaft assembly according to the bending dimension; the method comprises the following steps: controlling a touch pen to click a curved screen to obtain a two-dimensional click coordinate, converting the two-dimensional click coordinate into a three-dimensional point of a space coordinate system, calculating a reference tangent vector and a normal vector of a tangent plane of the point, rotating the tangent vector to a set angle to obtain an axial vector, establishing a local coordinate system and associating the local coordinate system with the space coordinate system; and controlling the test arm to move the touch pen to a target position and execute touch operation, and judging the touch state of the curved screen according to the touch test data. Accurate inclined touch control of any point of the curved screen is realized, driving scene man-machine interaction is truly restored, and test coverage and accuracy are improved.

The invention relates to a closed-loop virtual test flight pre-evaluation method and a medium, and relates to the field of flight tests. The method comprises the steps of constructing a digital twin module which comprises a pneumatic sub-model, a flight control sub-model, a power sub-model and a structure sub-model, defining a tilt transition specific high-risk subject and generating a test case, executing parallel Monte Carlo simulation and hardware-in-the-loop test, performing flight safety risk identification and envelope boundary quantification, and determining a tilt transition specific high-risk subject according to the tilt transition specific high-risk subject. And generating a risk assessment report and optimizing a real aircraft test flight outline. Wherein the aerodynamic sub-model adopts a dynamic vortex grid correction method based on CFD offline calibration and online query; the flight control sub-model comprises a configurable fault injection module based on a script engine, and the configurable fault injection module is used for defining a coupling fault sequence of sequential logic and a condition triggering relation. Compared with the prior art, the accuracy and the applicability of the pre-evaluation of the virtual test flight are improved.

The invention discloses a method for actually measuring and checking network-related characteristic parameters of a new energy and energy storage power station, and the method comprises the steps: S1, building a semi-physical simulation test system, and carrying out the hardware-in-the-loop test of a to-be-tested control system, so as to obtain dynamic characteristic data; s2, performing parameter identification based on the dynamic characteristic data to establish a single-machine model; s3, performing a simulation test on the single-machine model, and if a transient error between simulation data and laboratory test data is within an allowable range, determining that the single-machine model passes verification; s4, identifying and verifying model parameters of the whole station level controller by referring to the steps S1 to S3, aggregating single machine models into a station level model, and acquiring whole station simulation data; s5, downloading the station-level model parameters and the control software to field equipment to obtain field actual measurement data; s6, if the deviation between the field actual measurement data and the simulation data meets the preset standard, it is judged that checking of the network-related characteristic parameters is completed. The method has the advantages of improving the parameter checking efficiency and the like.

The embodiment of the invention provides a test environment deployment method and device, a medium and a program product, and relates to the technical field of hardware-in-loop testing. The method comprises the following steps: acquiring a test requirement and a template library, wherein the template library comprises an environment configuration template and a parameter rule; generating environment configuration based on the test requirement and the template library, wherein the environment configuration comprises an operating system version, a network parameter and a resource allocation parameter; and deploying a test environment according to the environment configuration, wherein the test environment is used for hardware-in-the-loop test. Based on the method, the test environment deployment process can realize high automation, the probability of errors caused by manual operation is reduced, and the deployment reliability is improved. And the test requirements can be dynamically adapted, the environment consistency and the resource utilization rate are improved, rapid generation and parameter optimization of the test environment are realized, the deployment time consumption is reduced, and the test environment deployment efficiency and the overall test efficiency are improved.

The invention discloses a closed-loop test system for a hardware-in-loop control air suspension. The closed-loop test system comprises an air suspension ECU to be tested; the simulation module is used for correspondingly simulating various vehicle parameters based on various vehicle parameter simulation models; the hardware simulation module is used for providing a hardware simulation signal for the air suspension ECU; the control module is used for controlling the simulation module and the hardware simulation module based on a test case when a test instruction is received, and outputting a target vehicle parameter and a target hardware simulation signal; the air suspension ECU performs closed-loop testing based on the target vehicle parameters and the target hardware simulation signals, so that real-time interaction and closed-loop logic among various modules in the dynamic state of the whole vehicle can be truly simulated, the simulation precision of the working condition of the air suspension is improved, an accurate test result is provided, and the test efficiency is improved. And the problems of high cost, long period, low repeatability and safety risk under limiting working conditions caused by real vehicle testing are avoided.

The invention provides an MCP2515CAN controller virtual simulation and integration method oriented to a hardware-in-the-loop test. The method comprises the following steps: constructing an MCP virtual model; a virtual CAN bus is constructed; constructing an external interface; for the MCP virtual model, creating an independent event, and realizing asynchronous data transceiving and interrupt processing by using an event triggering mechanism; the MCP virtual model, the virtual CAN bus and the external interface are integrated in a unified simulation environment. The technical problems that a traditional controller communication test depends on real hardware, the cost is high, debugging is complex, and compatibility is poor are solved.

The invention discloses an SVG voltage ride-through control parameter identification method based on a kernel extreme learning machine in a double-solution space, and the method comprises the following steps: S1, dividing SVG fault stages, building an SVG steady-state control model and a fault control model, and according to the difference of the influence of control parameters on steady-state characteristics and fault characteristics, carrying out the recognition of SVG voltage ride-through control parameters; dividing a solution space of SVG control parameters into a double-solution space composed of a steady-state parameter solution space and a dynamic parameter solution space; s2, extracting a corresponding observed quantity characteristic value, constructing an input-output sample, and establishing a kernel extreme learning machine model in a double-solution space; s3, training a kernel extreme learning machine by using the input-output samples, and inputting RT-LAB hardware in-loop test data into the trained kernel extreme learning machine to identify SVG control parameters; according to the method, the adaptability and the accuracy of identification are improved, so that accurate modeling of the SVG is realized.

The invention relates to the technical field of computers, and discloses a bus signal simulation method for a universal emission control system. The method comprises the following steps: acquiring equipment node topology, a protocol type and historical load data; constructing a bus network abstract model; extracting a message flow time sequence template; generating a concurrent message scheduling sequence conforming to the arbitration logic; fusing to form a high-fidelity signal substrate; superposing physical layer interference signals based on measured data; and the data is injected into a tested system through a hardware-in-the-loop interface. The system comprises a bus topology analysis module, a network modeling module, a time sequence template extraction module, a scheduling generation module, a signal fusion module, an interference injection module and a hardware output module. According to the method, through logic and physical layer combined modeling, the test authenticity, the coverage rate and the platform universality are remarkably improved.

The application discloses a kind of hardware-in-the-loop test of automatic driving domain controller, comprising: real-time processor and graphics workstation;Graphics workstation is used to generate simulation traffic scene information, simulation sensor information is generated based on simulation traffic scene information, first simulation sensor information in simulation traffic scene information and simulation sensor information, simulation traffic scene information and simulation sensor information are transmitted to automatic driving domain controller, second simulation sensor information in simulation sensor information is transmitted to real-time processor;Real-time processor is used to transmit second simulation sensor information to automatic driving domain controller, receives the vehicle control information that automatic driving domain controller feedback.This application provides the hardware-in-the-loop test system, device, storage medium of automatic driving domain controller, can avoid the problem that scene information and sensor perception information do not match when hardware-in-the-loop test, improves the accuracy of test.

The invention relates to a message verification method and device and a vehicle, relates to the technical field of hardware-in-the-loop testing, and aims to solve the problem of difference between original data of a bottom layer of a controller and data processed by an application layer. The method comprises the following steps: acquiring message description information corresponding to a target message sent by a controller in a hardware-in-the-loop test process of the controller; determining whether the message description information comprises target information or not; wherein the target information is used for indicating the data bit without the signal value in the target message. And under the condition that the message description information does not comprise the target information, generating the target information. And updating the target information to the message description information. And the updated message description information is utilized to perform message verification on the target message, so that the problem of data difference between a bottom layer and an application layer can be solved, and the efficiency and reliability of system development are improved.

The application provides a key learning test method, system, device, equipment and readable storage medium. It relates to the technical field of testing and aims to solve the problem of low accuracy of testing key learning algorithm. The method comprises the following steps: based on the message simulation of the sending logic of the auxiliary driving system ADAS by the upper computer, an environment model file for key learning test is obtained, the environment model file comprises a key SKC and a security code SC; based on the upper computer, the environment model file is compiled in a hardware-in-loop HIL device; based on the upper computer, an executable file is generated according to the environment model file; based on the upper computer, the executable file is sent to the HIL device; based on the HIL device, the key learning test of the battery management system BMS is performed by using the executable file. The application can improve the accuracy of testing.

The application provides a test method of a power grid based on RTDS and energy storage signal interaction simulation system, comprising: running a real-time digital simulation system, and issuing a start-up instruction by a storage converter; a battery model real-time simulation machine in a hardware-in-the-loop test system charges according to the start-up instruction; the frequency of a power grid model in a real-time simulation host is adjusted to a trigger threshold of primary frequency modulation, and a discharge instruction is issued by the storage converter; the battery model real-time simulation machine outputs active power according to the discharge instruction, and discharges according to the discharge current, and the discharge process is fed back to the real-time digital simulation system through a battery management system. The application also provides a power grid based on RTDS and energy storage signal interaction simulation system. Through the real-time digital simulation system, the storage converter, the hardware-in-the-loop test system and the battery management system, synchronous simulation of the power grid-energy storage is performed, and a real application scenario of charging, discharging, start-up and shutdown real-time adjustment of the energy storage container during grid connection is simulated.

The invention relates to the field of aviation electrical engineering and real-time simulation testing, and provides a multi-level collaborative verification method and platform for an aircraft power generation system control strategy and a storage medium, and the method comprises the steps: an offline simulation stage: carrying out the preliminary design and verification of the control strategy; in the real-time simulation stage, closed-loop real-time verification and parameter optimization are carried out on the control strategy; in the rapid prototyping stage, optimized control strategy codes are deployed to a rapid prototyping controller and are connected with real or high-precision simulated power generation system hardware, and hardware-in-loop-entity hybrid verification is carried out; wherein a unified performance reference and error feedback chain penetrating three stages of off-line simulation, real-time simulation and rapid prototyping is established, a verification result of each stage is used as an expected reference of the next stage, and error monitoring and backtracking correction are carried out. According to the method, through offline-real-time-prototype three-layer progressive verification and a model precision progressive calibration mechanism, the confidence coefficient and the one-time success rate of final physical verification are greatly improved.

The invention relates to the technical field of fault diagnosis, in particular to a charging pile main power circuit fault diagnosis system construction method based on a digital-physical hybrid platform, and the method comprises the steps: constructing a fault database based on historical fault data; diversified fault features are injected into a charging pile main circuit discrete model in the core processing module through a random extraction strategy, and a fault reaching the standard is dynamically forbidden in combination with a closed-loop verification mechanism, so that a diagnosis model continuously adapts to an unknown fault type. Fault diagnosis models in a core processing module and an auxiliary processing module in an upper computer are respectively optimized by verifying diagnosis results, fault library dynamic injection is combined with double-level diagnosis verification, the limitation of center AI static modeling in the prior art is broken through, and a digital-physical hybrid verification closed loop is constructed, so that the fault diagnosis accuracy is improved. The two times of verification and optimization of the charging pile fault diagnosis model in the hardware-in-the-loop are realized, and the accuracy and the real-time performance of the fault diagnosis of the charging pile main power circuit under the complex working condition are comprehensively improved.

The utility model relates to the technical field of automobile controller testing, in particular to a controller hardware-in-the-loop test simulation system, which comprises a tested controller, a hardware-in-the-loop test simulation system and a hardware-in-the-loop test simulation system, the processor is connected with the tested controller; the first board card is connected with the processor; the simulation load, the real load, the second board card and the third board card are connected with the first board card; the upper computer is connected with the processor; a programmable power supply; and the connector is connected with the first board card. Therefore, the problem that hardware-in-the-loop HIL test equipment of an existing controller cannot meet the test requirement of the PCCU of the power chassis integrated controller is solved.

The application belongs to the technical field of power systems, and specifically discloses a wind turbine transmission chain test platform simulation method based on controller hardware-in-the-loop, which comprises the following steps: designing wind turbine parameters, constructing a wind turbine simulation model; establishing a wind farm model and embedding it into the wind turbine simulation model; constructing a transmission chain model and connecting it with the wind turbine simulation model; constructing a control system comprising a main controller model and a subsystem control system, and establishing a control instruction channel and a feedback signal channel between the subsystem control system and the transmission chain model; deploying the control system in a fast control prototype and connecting it with the simulation platform through a physical interface; collecting transmission chain operation data during the simulation process, and evaluating the control strategy of the test platform and the performance of the transmission chain. The application utilizes hardware-in-the-loop simulation technology to realize closed-loop operation between the controller entity and the virtual model, effectively improving the authenticity of the control strategy verification of the transmission chain test platform and the flexibility of the test platform debugging.

The application relates to an FPGA prototype verification method and system of a smart meter chip, and belongs to the field of integrated circuit testing and electric power metering. The method aims to solve the problems of ASIC design transplantation to an FPGA platform, large difference between a verification environment and a real power grid, and lack of a real-time closed-loop verification mechanism. A technical scheme efficiently transplants the design to the FPGA by optimizing ASIC front-end synthesis constraints and adopting a netlist-level IP replacement strategy; a hardware-in-the-loop system is constructed, which comprises a real power grid signal source, a separation device simulation front end, an FPGA verification board, a high-precision standard electric energy meter and a host computer. The system can generate a real power grid excitation and realize synchronous collection of prototype output and the standard meter, real-time error analysis and dynamic adjustment of parameters, thereby forming a closed-loop verification. The application significantly improves code transplantation efficiency, provides a highly consistent real power grid verification environment, and greatly improves verification iteration and defect positioning speed.

The invention relates to the technical field of aviation electrical system design and verification, and provides an aircraft power distribution system controller rapid prototype design method and system based on multi-level hardware-in-loop verification, and the method comprises the steps: S1, an architectural offline simulation stage: carrying out the preliminary function verification and parameter setting of a control logic through a unified simulation model; s2, in a distributed real-time simulation and code generation stage, real-time closed-loop verification and iterative optimization are carried out on control logic; and S3, a hardware replacement type rapid prototype verification stage: performing performance verification and final setting on the control strategy under a highly approximate real working condition. The method provided by the invention not only can greatly reduce the safety risk in the physical test, but also has the remarkable advantages of short development period, low verification cost and support of multi-level integrated verification, thereby providing reliable experimental data support for the subsequent physical verification of the aircraft power distribution system control strategy.

The embodiment of the invention provides an equipment scheduling method and device based on a hardware-in-the-loop test, electronic equipment and a storage medium. The method comprises the steps that equipment parameters of current test equipment are acquired; according to pre-determined pre-estimated planning information, determining a target test case corresponding to the device parameters, the pre-determined pre-estimated planning information comprising a test device and a test case corresponding to the test device, and the pre-estimated planning information being a test case corresponding to the test device according to historical test data; determining the estimated time and the corresponding estimated value of the test case on each test device, so that the estimated time meets the preset average time and the estimated value is greater than the preset value; the target test case is sent to the current test equipment, so that the execution time for executing the target test case tends to the preset average time, the estimated value is maximum, the state of the test equipment can be comprehensively considered, the test equipment and the test case are reasonably configured, and the test efficiency is improved.