9772 results about "High energy" patented technology

The invention relates to the technical field of storage equipment management, in particular to an intelligent control method and system for storage equipment, and aims to solve the problems of task allocation, path optimization and equipment collaboration in a complex storage scene. According to the method, a storage equipment function model comprising an upper-layer frame model and a lower-layer equipment model is constructed, task allocation and path planning are optimized by using a neural network model in combination with task requirements, and a storage equipment control instruction is generated. In the task execution process, task priorities and path planning are adjusted in real time to adapt to dynamic environment changes, and it is ensured that tasks are completed efficiently. According to the method, a task distribution diagram and a path planning scheme are further optimized through a dynamic task diagram and a dynamic energy field, the problems of equipment congestion, too high energy consumption and task delay are effectively solved, the collaboration efficiency and the resource utilization rate of storage equipment are improved, and the method is suitable for various complex storage scenes.

The invention provides a self-adaptive power supply energy-saving configuration method and system based on energy gradient utilization, and relates to the technical field of power supply management, and the method comprises the steps: collecting the operation parameters of electric equipment, building a power utilization model, and carrying out the self-adaptive correction; constructing a multi-stage energy distribution matrix according to the corrected power utilization model, and performing energy efficiency grading on the power utilization equipment; performing spatial-temporal feature extraction by adopting a bidirectional attention mechanism, generating an electric equipment priority strategy in combination with a self-calibration network, and further calculating an energy distribution proportion of each level of electric equipment; and finally, generating a control signal according to the energy distribution proportion, adjusting the power supply power of each stage of electric equipment, distributing the exceeded power to the electric equipment with the secondary high energy conversion efficiency when the power value exceeds a target power threshold value, and outputting a self-adaptive energy balance control instruction according to the prediction control model to adjust the operation state of the electric equipment.

The invention discloses a lithium iron phosphate positive electrode material, a preparation method thereof and a lithium battery, and relates to the technical field of lithium ion batteries. According to the method, the pressing index of the lithium iron phosphate positive electrode material is tested by adopting a specific method, so that the pressing index meets a specific range, meanwhile, the average circularity of larger particles in a Dv50-Dv100 range meets a proper range, the lithium iron phosphate positive electrode material has better particle movement capability, and the particles can move at a higher speed to be rearranged during pressing, so that the particle size of the lithium iron phosphate positive electrode material is reduced, and the quality of the lithium iron phosphate positive electrode material is improved. Therefore, the positive pole piece with high compaction density can be obtained, the charge-discharge capacity of the battery can be improved, and meanwhile, the particles can be prevented from being broken when being pressed, so that the positive pole piece has good anti-pressure capability. By adopting the lithium iron phosphate positive electrode material provided by the invention, the lithium battery has relatively high energy density and capacity retention ratio.

The invention discloses an energy-saving control method and system for an airplane ground air conditioning unit, and belongs to the technical field of air conditioning system energy saving.The method comprises the steps that internal and external environment parameters of a cabin are collected in real time, temperature prediction is conducted based on the internal and external environment parameters of the cabin, and a predicted temperature change curve is constructed; running state parameters of the aircraft ground air conditioning unit are called, dynamic energy-saving control is carried out in combination with the predicted temperature change curve, and an energy-saving control strategy is formulated; cabin internal variable parameters are introduced to optimize the energy-saving control strategy, and an optimized energy-saving control instruction set is generated; and the optimized energy-saving control instruction set is executed for cooperative driving, cooling circulation is conducted according to the cooperative driving result, and self-adaptive energy-saving control over the aircraft ground air conditioning unit is achieved. The technical problems of high energy consumption, unstable temperature control and low equipment operation efficiency caused by the lack of precise response capability of an air conditioning unit to dynamic changes of internal and external environments of a cabin in the prior art are solved.

The invention relates to the technical field of video monitoring, and discloses a camera cooperative monitoring method and system based on multi-modal perception, and the method comprises the steps: detecting an abnormal event signal in an environment through a non-visual sensor node, triggering the activation of a camera, and carrying out the visual capture of a target region; the camera performs relay tracking based on target feature matching to generate a continuous motion track; performing multi-view collaborative shielding on privacy sensitive information in the tracking target, generating desensitized monitoring data, and uploading the desensitized monitoring data; and optimizing the energy consumption of the camera in a non-event triggering period, and updating the behavior recognition model based on the desensitization data. According to the method, the contradiction between privacy protection and monitoring efficiency is solved, cross-regional model evolution and energy consumption reduction are realized, and the problems of response lag, data redundancy, privacy disclosure and high energy consumption of traditional monitoring are systematically avoided.

The invention discloses a repetition-frequency-adjustable high-energy nanosecond laser and a working method thereof, and belongs to the technical field of lasers. The laser comprises a synchronizing signal controller, a nanosecond seed source, an electro-optical selection system, a first end face pumping amplification stage, a second end face pumping amplification stage and a side face pumping bi-pass amplification stage, the synchronizing signal controller is adopted to generate a clock reference signal, a frequency division synchronizing signal and a clock synchronizing signal, and integrated control over system signals is achieved. The clock reference signal is used for triggering the seed source to generate nanosecond seed light pulses, the frequency division synchronizing signal is optimized and adjusted to control the electro-optical menu system to screen out frequency division seed light pulses, and the repetition frequency of the seed light pulses is adjustable. Meanwhile, a pulse pumping mode MOPA structure is adopted, the repetition frequency of each amplification stage pumping light pulse and the repetition frequency of the non-frequency-divided seed light pulse are kept consistent through a clock synchronization signal, it is ensured that the heat effect of the whole system is stable, and repetition frequency adjustable nanosecond laser output with high energy and good reliability is achieved.

The invention relates to the technical field of energy storage management, in particular to a high-energy-density liquid cooling energy storage system based on thermal management optimization, which comprises a thermal response calculation module, a thermal risk area identification module, a cooling resource allocation module, a thermal decoupling state judgment module and a charging and discharging power limiting module. According to the method, the inlet temperature, the outlet temperature and the cooling liquid flow speed of the high-energy-density energy storage equipment are obtained, the unit thermal load conversion rate is calculated, the unit thermal response deviation degree is determined, the thermal risk area higher than the standard limit is clearly recognized in the energy storage equipment, the corresponding liquid cooling channel is accurately selected, and the cooling liquid pulse flow frequency is optimized; the pertinence and timeliness of the cooling liquid in actual use are effectively improved, the local overheating hidden danger is avoided, the lag response is marked in time by monitoring the cooling liquid pressure difference and the temperature rise change in real time, the decoupling state between the cooling liquid and the thermal load is judged, the charge and discharge power dynamic reduction measure is implemented, and the trend of abnormal and continuous accumulation of the local thermal load is restrained.

The invention discloses an energy consumption prediction and scheduling control method based on machine learning. According to the method, operation parameters, energy consumption curves and environment disturbance data of multiple devices are collected through a distributed sensing terminal, the data are input into a pre-trained machine learning model, and a probability prediction result of future energy consumption distribution is generated. On the basis of prediction, an intervention signal is applied in an equipment safety boundary, equipment response characteristics are obtained according to the difference before and after intervention, and an energy consumption risk map is constructed by combining the equipment response characteristics with a probability prediction result. And based on the energy consumption risk map, generating an extreme disturbance scene by using digital twinning, performing consistency check on a probability prediction result and a scheduling scheme in a data domain and a physical domain, and performing multi-stage scheduling in combination with task delays to generate a scheduling result. And finally, issuing the scheduling result to the equipment. The method can improve the accuracy of energy consumption prediction and the reliability of scheduling decision making, and is suitable for intelligent management of data centers, industrial production and high-energy-consumption scenes.

The invention relates to a battery monomer, a battery device and a power utilization device, the battery monomer comprises an electrode assembly and an electrolyte, and the electrode assembly comprises a positive pole piece and a negative pole piece; the positive pole piece comprises lithium-containing phosphate with an olivine structure; the negative pole piece comprises graphite particles; the electrolyte comprises a carboxylic ester solvent and a first additive, the thickness of the single-side negative electrode film layer is 50 microns to 75 microns, and the volume average particle size of the graphite particles is 8.5 microns to 13.5 microns; based on the mass of the electrolyte, the mass content of the carboxylic ester solvent is 8%-60%, the total mass content of the first additive is 3%-10%, the first additive comprises 1, 3-propane sultone with the mass content larger than or equal to 0, an ethylene carbonate derivative with the mass content larger than or equal to 0 and vinylene carbonate with the mass content larger than or equal to 3%, and the ethylene carbonate derivative comprises a compound shown in the formula A. According to the invention, the rapid charging performance and the cycle performance of the battery monomer under high energy density can be improved. # imgabs0 # formula A

The invention relates to the technical field of mechanical arm control, and particularly discloses a multi-axis motion control method based on a six-axis hydraulic mechanical arm, and the method comprises the following steps: establishing a kinetic model and a hydraulic system model of the six-axis hydraulic mechanical arm, generating a motion track in a Cartesian space or a joint space based on a preset task demand, and generating a multi-axis motion model of the six-axis hydraulic mechanical arm; the track smoothness is optimized through an S-type acceleration and deceleration algorithm; a deviation coupling synchronous control strategy is adopted, and position, speed and pressure signals of all hydraulic cylinders are collected in real time. According to the multi-axis motion control method based on the six-axis hydraulic mechanical arm, through multi-layer modeling, multi-algorithm fusion and intelligent optimization, the core problems of synchronous errors, non-linear interference, high energy consumption and the like in multi-axis cooperative control of the hydraulic mechanical arm are solved, high-precision, high-robustness and low-energy-consumption industrial-grade motion control is achieved, and the multi-axis motion control method is suitable for industrial production. The method is suitable for heavy-load carrying, precision assembling and other complex scenes.

The invention discloses an energy-efficient task scheduling method for an edge computing system, which comprises the following steps of: acquiring a task state, a computing node resource state, a link state and an energy consumption state according to a unified time slot under a computing power network control domain, and constructing a system state vector; performing priority evaluation on the to-be-scheduled task based on the residual delay budget, the candidate node energy efficiency coefficient and the queue position to obtain a target task set; inputting a system state vector and a target task set into an energy efficiency perception deep reinforcement learning scheduling model, outputting a task-node allocation decision under the constraint of computing node resources and task time delay, and introducing a system-level energy consumption ratio, self-adaptive energy consumption penalty and exploration bias facing high-energy-efficiency nodes into rewards; and scheduling tasks according to the allocation decision, recording state transition and instant rewards, updating a double-commentator and actor network, and performing iterative execution in continuous time slots. According to the method, task success rate, time delay, load balancing and energy-saving performance are considered, and system energy consumption is reduced.

The invention discloses an AI computing power equipment intelligent energy consumption management system and method based on big data, and relates to the technical field of data center energy consumption management, the method comprises the following steps: obtaining real-time operation data of AI computing power equipment, the real-time operation data comprising load characteristic parameters, energy consumption characteristic parameters, environment characteristic parameters and equipment state parameters; obtaining a load discrimination value according to the load characteristic parameter; obtaining an energy consumption discriminant value according to the energy consumption characteristic parameters; acquiring an environment discrimination value according to the environment characteristic parameters; acquiring a state discrimination value according to the equipment state parameter; fusing the load discriminant value, the energy consumption discriminant value, the environment discriminant value and the state discriminant value to generate a comprehensive energy efficiency index; judging whether the comprehensive energy efficiency index exceeds a preset dual-threshold decision interval or not; if the upper limit threshold value is exceeded, triggering graded consumption reduction response, including dynamic frequency modulation, task migration or equipment dormancy; and if so, determining that the current operation mode is in a high-energy-efficiency state and maintaining the current operation mode.

A system and method for enabling real-time dispatch of flexibility resources to unlock grid capacity through AI-based orchestration. The invention addresses the challenge of connecting high energy demand users, such as data centers, to constrained electricity grids without requiring infrastructure upgrades. The system establishes a marketplace where flexible asset holders set temporal compensation prices and boundary conditions, enabling true market-based participation. An AI orchestration engine analyzes real-time grid conditions and modifies flexible asset behavior to create inverse consumption profiles that counterbalance new demand loads. The platform integrates hardware and software solutions for remote control and APIs for autonomous systems like electric vehicles. Aggregators and off-takers can establish long-term contracts for flexible capacity at agreed prices. The AI system ensures flexible assets meet user-defined boundary conditions while simultaneously masking high energy demand, making new loads invisible to the grid and enabling immediate connection of data centers essential for industrial deployment.

The invention belongs to the technical field of cleaning and dirt prevention and removal, and discloses a control system and a control method of an ultrasonic cleaning device, stable energy coupling and dead-corner-free cleaning are realized through double-closed-loop driving and dynamic modulation in an ultrasonic cleaning link, and the uniformity of tank liquid cavitation intensity is remarkably improved. Meanwhile, control strategies are customized in the aspects of a rinsing link, a water cutting and drying link, liquid level control, manipulator control and the like, so that the defects of high energy consumption, incomplete drying, low rinsing efficiency, manipulator conflict and the like in the prior art are overcome while the surface and the interior of the workpiece are thoroughly cleaned; and the cleaning effects of high cleanliness, complete drying and no physical or chemical damage are ensured.

The embodiment of the invention provides a secondary battery monomer, a secondary battery and a power utilization device, the secondary battery monomer comprises a laminated electrode assembly, the laminated electrode assembly comprises a positive pole piece, a negative pole piece and an isolation film, the positive pole piece comprises a positive pole film layer, the positive pole film layer comprises a positive pole active material, the negative pole piece comprises a negative pole film layer, and the isolation film comprises a negative pole active material; the negative electrode film layer comprises a negative electrode active material; the positive electrode active material comprises lithium-containing transition metal phosphate and lithium-containing transition metal oxide; and the thickness h of the isolating membrane is more than or equal to 8 microns and less than or equal to 21 microns. The secondary battery cell can give consideration to both high energy density and good safety performance.

The invention discloses a high-voltage power distribution cabinet heat dissipation system based on big data, which relates to the technical field of heat dissipation of electrical equipment and comprises a data acquisition module, a processing analysis module, a man-machine interaction module and a data storage module. An existing heat dissipation mode usually depends on a static fan or air conditioning equipment, dynamic adjustment cannot be carried out according to environment changes and load conditions, and the problems of high energy consumption and slow response exist. The system processes data, eliminates abnormal values, fills missing data, calculates correlation among temperature, humidity, current and fan rotating speed, predicts change trends of the temperature, the humidity and the current through a time sequence model, and displays key data through a graphical interface by a man-machine interaction module, so that the equipment management efficiency is improved; and precious historical data is provided for subsequent fault analysis and tracking, so that optimization of a maintenance strategy of the system and reduction of potential operation risks are facilitated.

The invention discloses a server power supply system and a server, relates to the field of server power supply, and is used for solving the problem of high energy loss in a traditional alternating current power supply architecture. The power conversion module converts the power supply into high-voltage direct current with the voltage not lower than the preset voltage, the high-voltage direct current is transmitted to the power distribution board of the server through the bus copper bar, and the bus copper bar serves as a transmission medium of the high-voltage direct current and has low resistance and high current-carrying capacity. Extra loss caused by electromagnetic induction and a capacitance effect in alternating current transmission is avoided; high-voltage direct current is directly input to the power distribution board, so that multiple times of conversion in an intermediate link are avoided, and energy loss in the conversion process is reduced; and the power distribution board directly converts the high-voltage direct current into the voltage required by the load, so that the loss of multi-stage conversion in the traditional architecture is reduced. According to the invention, the power transmission efficiency is improved, the energy loss is reduced, and the requirement of a modern high-computing-power and high-energy-consumption server for efficient power supply is met.

The invention relates to the technical field of sewage treatment, and discloses a supervision system and method for a sewage treatment process, and the system comprises a multi-parameter real-time monitoring module, a data fusion and analysis module, an automatic dosing control module and a feedback optimization module. The method is applied to the system. According to the supervision system and method for the sewage treatment process, dynamic and accurate supervision of the sewage treatment process is realized through the synergistic effect of the multi-parameter real-time monitoring module, the data fusion and analysis module, the automatic dosing control module and the closed-loop feedback optimization module; the problems of parameter simplification, control lag, high energy consumption and the like in the prior art are solved, the standard reaching rate of effluent is increased, and meanwhile, the agent cost and the equipment maintenance cost are reduced.

The invention relates to a silicon-carbon composite material and a preparation method and application thereof.The preparation method comprises the steps that a porous graphite raw material is subjected to acid pickling and smashing to obtain pretreated porous graphite, then the pretreated porous graphite is soaked in a carbon precursor solution in a vacuum mode, carbonization treatment is conducted after centrifugal separation, pores of the porous graphite are filled with carbides, physical activation is conducted, and the silicon-carbon composite material is obtained; the preparation method comprises the following steps: forming pores in a carbide to form a graded pore structure to obtain a porous graphite composite material, then carrying out silicon deposition in a fluidized bed to obtain a uniform nano silicon layer, and then carrying out carbon coating treatment to obtain a silicon-carbon composite material; the graphite with relatively low cost is adopted as a matrix, high capacity and long cycle performance of the graphite-based silicon-carbon negative electrode material are realized through hierarchical pore structure design, carbonization-activation synergistic pore forming and interface deposition process optimization, and the graphite-based silicon-carbon negative electrode material can be applied to the fields of power batteries and high-energy-density energy storage, especially the field of lithium ion batteries and has wide application prospects. The expansion rate of the battery can be reduced, and the specific capacity, cycling stability and safety of the lithium ion battery can be improved.

The invention relates to the technical field of robots, and provides a parallel connection rod driving mechanical finger with four degrees of freedom, which comprises a base, and a first driving mechanism, a second driving mechanism, a third driving mechanism and a fourth driving mechanism which are arranged on the base in parallel, the mechanical finger further comprises an MCP joint, a PIP joint and a DIP joint which are connected in sequence. The MCP joint is connected with the base through a universal joint. The first driving mechanism and the second driving mechanism are connected with the two sides of the MCP joint correspondingly so as to drive the MCP joint to conduct pitching motion and side-sway motion. The third driving mechanism is connected with the PIP joint so as to drive the PIP joint to perform pitching motion; and the fourth driving mechanism is connected with the DIP joint so as to drive the DIP joint to perform pitching motion. Four degrees of freedom have high dexterity, and the repeated positioning precision is good; high load ratio, high rigidity and high energy density are achieved, the branch chain structure interchangeability is good, the overall structure is simple and compact, and the space occupation ratio is small.

The invention discloses a preparation method of a silicon-carbon material for a negative electrode of a lithium ion battery, and relates to the technical field of lithium ion batteries, and the preparation method comprises the following steps: (1) selecting a specific silicon source solute and an organic solvent to prepare an organic silicon source solution; (2) selecting porous carbon as a substrate, and carrying out vacuum impregnation treatment in a silicon source solution; (3) carrying out solvothermal silicon deposition reaction on the porous carbon impregnated with the silicon source solution in a high-pressure reaction kettle; (4) carrying out vacuum impregnation on the deposited silicon porous carbon subjected to solvent heat treatment in a carbon source organic solvent; and (5) cracking and carbonizing the deposited silicon porous carbon impregnated with the carbon source solvent at a high temperature to form the composite silicon carbon material with carbon-coated silicon crystal particles. According to the present invention, the energy density of the lithium ion battery negative electrode material is improved while the cycle life and the rate capability are significantly improved, such that the prepared silicon-carbon material has excellent electrochemical performance, and can well meet the application requirements of the lithium ion battery on the aspects of high energy density, long cycle life, high-rate charge-discharge and the like.

The present invention relates to the technical field of forging, and particularly to an automated piston forging feeding robot. The automated piston forging feeding robot comprises a sliding mechanism, a supporting mechanism, a base, a telescopic mechanism, a pushing mechanism, and a gripping mechanism, wherein the sliding mechanism is fixedly mounted on a walking beam, the supporting mechanism is fixedly mounted at a lower end of the sliding mechanism, the base is movably mounted on the ground, the telescopic mechanism is fixedly mounted in the supporting mechanism, the pushing mechanism is fixedly mounted on the ground, and the gripping mechanism is fixedly mounted at a front end of the walking beam. The present invention solves the problems of the high maintenance costs and high energy consumption associated with existing hydraulic feeding methods, achieves the ejection of billets during device movement, and provides appropriate cooling to prevent sticking. When billet jumping occurs, the hydraulic feeding methods fail to grip a workpiece, which causes the workpiece to remain in a deviated state and results in a failure to correct the position of the workpiece for delivery to a forging area for further processing. The present invention suppresses billet jumping and corrects the position of the workpiece.

The invention provides a manganese-based composite positive electrode material and a preparation method and application thereof. The manganese-based composite positive electrode material has a core-shell structure; the core of the core-shell structure is made of a lithium manganate material, and the shell is made of a lithium-rich manganese-based positive electrode material. Compared with the prior art, a manganese-based composite positive electrode material precursor with the inner core mainly comprising manganese and the outer shell mainly comprising nickel, cobalt and manganese is prepared in situ by adopting a coprecipitation method, and then pre-oxidation, lithium mixing and sintering modification are performed; the high-capacity, high-safety, long-circulation and high-compaction manganese-based composite positive electrode material of which the core is the lithium manganate material and the shell is the lithium-rich manganese-based positive electrode material is obtained, so that the problems of cycling stability and high-temperature storage of the manganese-based positive electrode material are solved; furthermore, the manganese-based composite positive electrode material is used as the positive electrode material of the lithium ion battery, so that the lithium ion battery with high energy density, long service life and high safety can be prepared.

The invention discloses a hydrogen cooling superconductive flywheel composite energy storage system, which relates to the technical field of new energy storage and comprises a superconductive flywheel energy storage module, a lithium battery energy storage module, a power conversion module, an intelligent control module, a cooling sub-module and a hydrogen energy recovery module, by combining the quick response characteristic of the superconducting flywheel and the high energy density of the lithium battery, the superconducting flywheel can realize quick energy storage and release by utilizing the friction-free characteristic of the superconducting flywheel, a cooling sub-module and a hydrogen energy recovery module are used, the cooling requirement of the superconducting flywheel is ensured, and meanwhile, energy recovery can be carried out; by utilizing the characteristic of high energy density of the hydrogen battery, the energy storage capacity of the composite energy storage system is further improved, and the limitation of a single energy storage technology on power density and energy density can be effectively solved through the hybrid energy storage system; and more reliable and efficient energy storage support is provided for the fields of power grid peak regulation, renewable energy source grid connection, electric automobiles and the like.

The invention discloses a soil resistance perception-based multi-mode adaptive subsoiling mechanism, which comprises an integral rack, a subsoiling monomer, a control system and an energy device, the subsoiling monomer detects soil resistance in real time through a sensor assembly and transmits the soil resistance to the control system, and the control system controls the subsoiling monomer according to the magnitude and change characteristics of the soil resistance. The subsoiler is automatically switched among three modes of traditional rigid connection subsoiling, self-excited vibration subsoiling and forced vibration subsoiling; when the soil resistance is smaller than a first preset threshold value, a rigid connection mode is adopted; when the resistance is between a first preset threshold value and a second preset threshold value, a self-excitation vibration mode is started; and when the resistance is greater than a second preset threshold value, the vibration motor is started to realize forced vibration. The control system not only monitors the resistance absolute value, but also analyzes the time characteristic to realize intelligent threshold adjustment. The problems that a traditional subsoiling mechanism is high in energy consumption and poor in adaptability are solved, and the intelligent subsoiling mechanism has the advantages of intelligent operation mode switching, optimized energy utilization, adjustable vibration parameters and the like.

The invention relates to the technical field of atmosphere lamp control, and discloses an audio analysis control method of a pickup atmosphere lamp and an atmosphere lamp thereof.The audio analysis control method of the pickup atmosphere lamp comprises the steps that the atmosphere lamp collects sound through a built-in sound receiving part, and the sound collected by the sound receiving part comprises music, music, music, music, music and the like; the sound is analyzed and processed through audio analysis, the audio analysis comprises sound preprocessing, the preprocessed sound is subjected to time domain feature extraction and frequency domain feature extraction to obtain the energy ratio of each frequency band of the sound, and each frequency band comprises a high-energy frequency band and a low-energy frequency band; and performing moving average filtering on the low-frequency-band energy to generate an energy envelope line. According to the invention, collected music signals are processed in real time through audio analysis, and information such as rhythm, frequency and intensity of music is extracted. The audio analysis technology ensures that light can be highly synchronized with music, and the user experience is improved.

The invention relates to the technical field of new energy, and particularly discloses a new energy heavy truck energy-saving path planning method and electronic device.The new energy heavy truck energy-saving path planning method comprises the steps that a layered road network based on an energy consumption model is constructed, and the layered road network divides a road into multiple levels through a comprehensive weight formula, wherein the high-level road network comprises low-energy-consumption main roads, and the low-level road network comprises all road types; and on the basis of vehicle real-time state parameters and destination information, a two-way A algorithm is adopted to carry out path search in the layered road network, the two-way A algorithm is synchronously expanded from a starting point and an ending point, and the search direction is optimized on the basis of a dynamic heuristic function. According to the new energy heavy truck energy-saving path planning method provided by the embodiment of the invention, three major pain points of high energy consumption, difficult energy complementation and poor real-time performance in new energy heavy truck path planning are optimized and solved through modules of layered road network construction, dynamic weight adjustment, bidirectional A * algorithm optimization and the like, and the energy complementation bottleneck problem of the new energy heavy truck is solved.

The invention provides a low-cost flow battery and an application thereof, a redox active substance of a positive electrode electrolyte of the low-cost flow battery contains a hydroxylamine cyclic structure group with hindered amine, and the hydroxylamine cyclic structure group with hindered amine is preferably selected from 1-hydroxy-2, 2, 6, 7, 8-tetramethyl-1, 3, 5-tetramethyl-1, 3, 5-tetramethyl-1, 3, 5-tetramethyl-1, 3, 5-tetramethyl-1, 3, 5-tetramethyl-1, 3, 5-tetramethyl-1, 3, 5-tetramethyl-1, one or more of a 1-oxo-2, 2, 6, 6-tetrasubstituted piperidine group, a 1-oxo-2, 2, 6, 6-tetrasubstituted piperidine group, a 1-oxo-2, 2, 6, 6-tetrasubstituted piperidine group, and a 1-oxo-2, 2, 6, 6-tetrasubstituted piperidinium group; a redox active substance of the negative electrode electrolyte contains one or more of a titanium element, a vanadium element, a chromium element, an iron element and a zinc element. The low-cost flow battery has the advantages of high output voltage, high energy density, environment friendliness and low cost, and has good application prospects and large-scale popularization potential in the field of energy storage.

A lithium-ion battery having excellent high-temperature storage and high-temperature cycling performance. The lithium-ion battery comprises a positive electrode, a negative electrode, and a non-aqueous electrolyte solution. The negative electrode comprises a negative electrode material layer containing a silicon-based material. The non-aqueous electrolyte solution comprises a lithium salt, an organic solvent, and an additive, the organic solvent comprising fluoroethylene carbonate, and the additive comprising a silane compound containing at least one carbon-carbon double bond. The lithium-ion battery satisfies the following conditions: 5≤(S*R) / (F*T)≤35, 5≤f≤15, 1.4≤R≤1.68, 9≤S≤18, and 0.01≤T≤0.5. According to the lithium-ion battery, the mass percentage content of the organic solvent and the additive in the non-aqueous electrolyte solution are controlled, and the mass percentage content of elemental silicon in the negative electrode material layer is controlled and the compaction density of the negative electrode material layer is controlled to be within a certain range, such that the lithium-ion battery has excellent high-temperature storage performance and an excellent high-temperature cycle life, while also taking into account high energy density.

The invention relates to the technical field of communication, and discloses a multi-parameter automatic detection system and method for laser communication equipment, and the method comprises the following steps: data collection and forward scattering compensation, feature extraction and modeling, virtual debugging and enhanced simulation, parameter optimization and noise filtering, and result verification and feedback adjustment. Through deep fusion of multi-mode sensing, intelligent modeling and closed-loop optimization, leap-over upgrade of laser communication parameter detection is realized, under the core breakthrough of signal-to-noise ratio improvement, the bit error rate of the system is reduced to a small magnitude, the transmission distance is synchronously extended to 182km, and through collaborative innovation of a federated learning framework and a digital twinning technology, the communication efficiency is greatly improved. The training efficiency is improved, the extreme working condition verification passing rate is improved, and meanwhile the ultrahigh energy efficiency ratio and the low annual failure rate are achieved.