9185results about "Electric devices" patented technology

The invention discloses a power battery health state on-line monitoring and early warning method and system based on multi-data fusion. The method comprises the following steps: synchronously acquiring multi-dimensional heterogeneous data in a battery operation process through a multi-sensor data acquisition module; carrying out standardization processing and preprocessing on the multi-dimensional heterogeneous data, extracting a comprehensive feature vector and carrying out multi-sensor data fusion; a multi-sensor data fusion algorithm is adopted to carry out weight distribution on the fused comprehensive feature vector, a dynamic weight coefficient is calculated according to the sensitivity and reliability of each parameter to the health state of the battery, and a fused battery state feature descriptor is obtained; and performing mode recognition and state classification on the fused battery state feature descriptors by using a pre-established evaluation model to realize quantitative evaluation of the health degree of the battery. According to the invention, real-time monitoring, evaluation and early warning of the health state of the battery in the whole life cycle are realized, and a reliable basis is provided for safe operation and maintenance decision of a battery system.

The invention relates to the field of power battery energy management, in particular to a power battery pack charging and discharging efficiency dynamic optimization system and method, and the system comprises a central control unit, a multi-dimensional sensing module, a dynamic charging and discharging control module, a working condition-heat dissipation cooperation module, a parallel cell equalization module and an aging adaptation optimization module. The multi-dimensional sensing module is used for collecting basic parameters, polarization characteristics, parallel state, aging degree and environmental parameters of a battery pack, the dynamic charging and discharging control module is used for collecting data, the working condition-heat dissipation coordination module adopts a three-stage heat dissipation framework, and the parallel battery cell balancing module is used for balancing the battery pack through a dynamic current distribution and voltage active balancing double-coordination mechanism. The aging adaptation optimization module is used for grading and differentially optimizing charge and discharge parameters and heat dissipation strategies based on the aging degree of the battery cell, so that the problems of low charge and discharge efficiency, poor wide temperature range adaptability, weak parallel consistency, fast aging attenuation and multi-factor coupling deterioration of the power battery pack are solved.

The invention relates to the technical field of charging control, in particular to a new energy automobile charging safety regulation and control method and system, and the method comprises the steps: collecting a multi-dimensional feature parameter set; acquiring battery health state and charge state information, and collecting multi-point temperature information on the surface of the battery; constructing the multi-dimensional feature parameter set into a multi-dimensional time sequence, performing statistical analysis on the multi-dimensional time sequence, and extracting dynamic feature indexes; performing structured fusion on the dynamic characteristic indexes, thermal field gradient parameters calculated according to multi-point temperature information and a multi-dimensional characteristic parameter set, and projecting the dynamic characteristic indexes, thermal field gradient parameters and the multi-dimensional characteristic parameter set to a key characteristic subspace through principal component analysis to obtain a charging response vector; generating a multi-dimensional security hyperplane through the dynamic security boundary model; continuously comparing the charging response vector with the multi-dimensional safety hyperplane, and calculating a safety margin scalar in real time; and inputting the safety margin scalar into the self-adaptive regulation and control model, and adjusting the charging current output. According to the invention, active predictive charging safety regulation and control are realized through multi-dimensional perception.

The invention discloses a new energy commercial vehicle fast charging working condition thermal management control method and system, and relates to the technical field of new energy vehicle thermal management and fast charging control, and the method comprises the following steps: collecting the temperature, voltage and current data of each subarea of a battery in a fast charging process, forming a time synchronization sequence, and based on the sequence, obtaining a new energy commercial vehicle fast charging condition; calculating internal thermal resistance and thermal capacity parameters of the battery in real time by using an online identification algorithm, updating a basic thermal model to obtain a corrected thermal dynamic model reflecting actual thermal characteristics of the current battery, importing the corrected model into a model prediction controller, constructing a multi-objective optimization function, and performing rolling solution in a prediction time domain to obtain a prediction model; and outputting an optimal target charging current instruction and a cooling total demand, adjusting the charging power according to the target current, and combining the temperature difference distribution of each partition. Accurate prediction and partition cooperative control of the thermal state of the battery in the fast charging process are achieved, the temperature rise and the temperature difference are effectively restrained while the charging efficiency is guaranteed, the service life of the battery is prolonged, and the system safety is improved.

The invention relates to the technical field of automobile brake control, in particular to a self-adaptive brake kinetic energy recovery control method and system based on multi-sensor fusion. Tire wear and road surface feature data are collected through a multi-source sensing fusion unit, and a tire wear coefficient and a road surface friction coefficient are generated through an intelligent decision calculation unit; the method comprises the following steps of: integrating the nonlinear correlation of the multi-source sensing fusion unit and the self-adaptive control execution unit through a rule and data fusion algorithm, outputting a comprehensive friction coefficient, and dynamically adjusting the braking kinetic energy recovery force and response time by the self-adaptive control execution unit according to the comprehensive friction coefficient. The system comprises a multi-source sensing fusion unit, an intelligent decision calculation unit, the self-adaptive control execution unit and a closed-loop feedback calibration unit. The closed-loop unit corrects data deviation through cross validation of the laser radar and the motor torque inversion model, the problems of poor working condition adaptation and unreliable data are solved, and the kinetic energy recovery efficiency, the braking safety and the driving smoothness are improved.

A vertical take-off or landing (VTOL) aircraft is disclosed that includes a propulsion system comprising at least four tilting propulsion assemblies and two or more lifting propulsion assemblies. Actuation of the tilting mechanisms can convert the aircraft from a hover configuration, in which all propellers produce thrust generally upward to counteract the aircraft's weight, to a forward flight configuration, in which the four or more tilting propellers produce thrust generally in a forward direction parallel to the fuselage to overcome drag in cruise flight and the lifting propellers produce no thrust or a level of thrust generally less than that required in the hover configuration.

The invention provides a new energy automobile high-voltage system dynamic risk assessment method and device based on multi-source data fusion, and is applied to the technical field of data processing. According to the method, data such as high-voltage component operation parameters, battery states, environment perception, fault history and whole vehicle control instructions are obtained. Pre-processing the first working condition label, the second working condition label and the third working condition label, analyzing a CONTROLSIGNAL field to obtain a working mode of the high-voltage system, and generating a dynamic working condition label; combining a Pearson's correlation coefficient and XGBoost feature importance, screening risk sensitive features from the two, and forming a risk related feature subset; the method comprises the following steps of: establishing an improved Bayesian network model, training a subset by using an improved Bayesian network model, establishing an exclusive risk assessment model for different working conditions, reasoning real-time data by using the model to obtain a probability value of each risk dimension, and generating a dynamic risk assessment result and an early warning signal in combination with grade standard judgment.

The invention relates to the technical field of electricity metering anomaly monitoring, and provides a distributed resource access-oriented lightweight electricity metering anomaly monitoring method, which comprises the following steps of: acquiring electrical data and environment associated data of distributed access points at an edge side, and constructing a fluctuation fingerprint feature vector; when it is detected that the fluctuation fingerprint feature vector meets a preset fluctuation triggering condition, based on Pearson correlation analysis between the electrical data and the environment associated data, performing decoupling and elimination on false anomalies caused by environmental factors to obtain a fluctuation fingerprint feature vector of non-environmental suspicious anomalies; based on historical normal operation data, constructing a normal working condition mode library by adopting a clustering analysis method, and determining a feature center and a dynamic safety radius of each normal working condition mode; and calculating the feature distance between the non-environmental suspicious abnormal fluctuation fingerprint feature vector and each normal working condition feature center at the edge side, and judging whether the electricity consumption metering is abnormal or not according to the relationship between the feature distance and the dynamic safety radius.

The invention discloses an electric vehicle charging monitoring method and device based on a heterogeneous feature fusion network, and the method comprises the steps: S01, collecting various time domain feature parameters and high-frequency key current signals of an electric vehicle battery in different charging states, and building a sample database; step S02, constructing an electric vehicle charging state prediction model, wherein the model comprises a time-frequency feature fusion network, a CNN-LSTM feature fusion module and a predicted value output module which are connected in sequence; step S04, the edge device receives the time domain characteristic parameters and the high-frequency key current of the tested electric vehicle battery in real time, and calls the deployed electric model for prediction to obtain a charging state prediction value; and S05, judging the abnormal charging state of the detected electric vehicle according to the state prediction value. The method has the advantages of being simple in implementation method, low in cost, high in monitoring precision, fast in early warning response, easy to apply on a large scale and the like.

This disclosure provides an improved universal interchangeable battery for electric vehicles forming part of a battery swapping ecosystem that includes electric vehicles, swappable batteries, a charging / swap station, a battery adaptor for reliable charging and communication, and a mobile application for managing battery swapping within a fleet and a network of charging stations, enabling efficient and user-friendly battery exchanges.

The invention relates to the technical field of automobile energy supply, in particular to a solid hydrogen storage-fuel cell integrated power assembly system based on dual-mode hydrogen supply, which comprises a hydrogen supply path identification module, a hydrogen storage unit state monitoring module, a linkage path switching module, a fuel cell load matching module and a safe hydrogen discharge regulation and control module. According to the method, the hydrogen supply pressure difference value is obtained by dynamically comparing the pressure of the cavity of the hydrogen storage tank with the pressure of the hydrogen inlet of the fuel cell, the current hydrogen supply path state can be accurately recognized in the early stage, rapid judgment of the hydrogen supply mode and accurate control of path switching are achieved, whether the risk of hydrogen supply interruption exists or not can be effectively screened, and the reliability of hydrogen supply is improved. The switching reliability of a hydrogen supply channel is improved through cross comparison of key state signals of a main channel and a standby channel, and instant response and energy consumption optimization of hydrogen discharge safety regulation and control are guaranteed through a linkage feedback mechanism between the hydrogen concentration change rate in unit time and catalytic converter control power.

The invention relates to the technical field of control and regulation, in particular to a new energy automobile battery health state prediction system which comprises a data acquisition module, a quantum feature evolution module, a digital twinning prediction module, a dynamic control module, a federal learning evolution module and a quantum verification module. The data acquisition module generates a spatio-temporal data base. The quantum feature evolution module outputs an ion desolventizing agent energy barrier change gradient, and the digital twinborn prediction module eliminates prediction offset through compensation and correction when the environment changes suddenly. The dynamic control module generates an environmental adaptation degradation suppression strategy. The federal learning evolution module encrypts transmission attenuation data and updates global model parameters, and the quantum verification module verifies the causality of a control instruction and rolls back to a safe steady state when the control instruction fails. The system forms quantum sensing, environment modeling, prediction compensation, risk suppression, model evolution and a safety verification closed loop, the battery life prediction precision in a dynamic environment is improved, and safety maintenance lag caused by environment sudden change is eliminated.

The invention relates to the technical field of intelligent automobiles, in particular to a battery performance test method and system for an intelligent automobile, and the method comprises the steps: obtaining the operation data of each single battery of the intelligent automobile under the current driving working condition and the working condition statistical data of the automobile, and constructing an input feature set, standardizing the input feature set, and inputting the standardized input feature set into a battery performance evaluation model to obtain key performance indexes of the single battery; dynamically adjusting a battery charging and discharging control strategy according to the key performance index and a real-time load demand under the current driving condition, verifying the accuracy of the key performance index by comparing the voltage fluctuation amplitude and the temperature change rate of the battery before and after adjustment, comparing with a preset safety threshold value, and if the threshold value range is exceeded, determining that the battery is in a charging state. If yes, generating corresponding performance early warning information; the method can adapt to complex and changeable driving working conditions of the intelligent automobile, and the precision and the real-time performance of battery performance evaluation are remarkably improved.

The invention discloses a permanent magnet synchronous motor temperature monitoring method based on digital-analog hybrid drive, and the method specifically comprises the steps: dividing a motor into a plurality of heat source nodes, including a stator winding, a stator tooth part, a rotor core and the like, connecting the nodes through a thermal resistance and thermal capacity network, building a thermal network model of the motor, and carrying out the thermal network model; calculating the initial values of thermal resistance and thermal capacity of each component of the motor, and optimizing parameters in a thermal network model by using a differential evolution algorithm based on the lumped parameter thermal network model and in combination with a data-driven strategy. Furthermore, temperature rise prediction is dynamically adjusted according to motor state data (such as stator current, rotating speed and the like) collected in real time so as to realize real-time temperature estimation. The method is high in temperature estimation precision, does not affect the performance of the motor, is simple in calculation, is good in real-time performance, and has physical interpretability. The temperature rise of the motor can be predicted in real time under different working conditions, early warning is given out, motor faults caused by too high temperature rise are effectively avoided, and the reliability and safety of the motor are improved.

A system for pre-charging short circuit detection in electric aircraft. The system includes a charging connector and a controller communicatively connected to the charging connector. The charging connector includes a housing, at least a conductor, and at least a control signal conductor. The housing is configured to mate with an electric aircraft port of an electric aircraft. The at least a conductor is configured to conduct a charging current to the electric aircraft. The at least a control signal conductor is configured to conduct a control signal. The controller is configured to receive a circuit health datum, through the at least a control signal conductor, prior to initiation of charging of the electric aircraft, and to disable initiation of charging of the electric aircraft if the circuit health datum comprises a short circuit datum. A method for pre-charging short circuit detection in electric aircraft is also provided.

The invention provides a new energy vehicle fault diagnosis and prediction method based on deep learning, and the method comprises the steps: collecting the brake intensity sudden change data in the operation of a new energy vehicle in real time, and determining the trend and amplitude range of the current brake intensity change according to the brake demand signals under various working conditions in combination with the historical fault mode record analysis, thereby achieving the fault diagnosis and prediction of the new energy vehicle. Obtaining a preliminary braking demand characteristic value; according to the braking demand characteristic value, calling a pre-established deep learning prediction model, analyzing the relevance between a historical fault mode and current braking strength sudden change data, calculating the probability distribution of feedback energy anomaly detection, and determining the potential fault risk level of the new energy vehicle; and for the potential fault risk level, acquiring real-time data of surface temperature scanning of the brake disc, identifying a thermal load area, analyzing temperature distribution uniformity, judging whether a key area exceeds a preset threshold value or not, and obtaining a thermal load state evaluation result.

The invention relates to the technical field of electric vehicle thermal management, discloses an electric vehicle motor and driver integrated intelligent cooling system and a control method, and aims at solving the problems that an existing motor driver thermal management system is low in cooling efficiency, high in energy consumption, complex and insufficient in space utilization rate. The method comprises the following steps: acquiring operation, thermal state and environment data; constructing a collaborative thermal model and predicting a thermal load; generating an optimal cooling strategy based on the predicted value and the target; the cooling liquid pump, the three-way valve and the cooling fan are adjusted, and cooling resources are dynamically distributed to achieve collaborative cooling. The system comprises a data acquisition module, a collaborative thermal model construction prediction module, an intelligent decision control module and an integrated cooling circulation execution module. By the adoption of the technical scheme, the cooling performance can be effectively improved, system energy consumption and complexity are reduced, space layout is optimized, the service life of parts is prolonged, and the reliability, the power performance and the endurance of the whole vehicle are improved.

The invention relates to the technical field of power consumption management, in particular to a pump station unit energy consumption real-time analysis system which comprises a load feature extraction module, a frequency stability recognition module, a start-stop window recognition module, a voltage response regulation and control module and a signal filtering module. According to the method, a sliding trend sequence is constructed through load state data and current increment information, slope abrupt change points are identified, trend direction classification is carried out, accurate identification of a frequency operation stability section is realized in combination with frequency variation amplitude, and a regulation and control time window is constructed through trend consistency judgment of energy consumption and flow in the same time domain. A voltage input strategy is set according to the trend change rate, a mapping table is formed, signal filtering and recovery are achieved through trend continuity judgment in confidence evaluation of energy consumption labels, and the behavior segmentation precision, the adaptability of electric energy input regulation and control and the continuity and controllability of overall operation state recognition in the energy consumption monitoring process are effectively enhanced.

The invention relates to an equalizing charge intelligent adjusting method for a power battery of a new energy automobile, which comprises the following steps of: acquiring a real-time state data set of each single battery from a power battery pack and carrying out filtering processing to acquire a state parameter sequence after filtering, the real-time state data set comprising voltage, temperature and charge state parameters; calculating a deviation value between each single battery and the group average value for the filtered state parameter sequence, and obtaining a deviation distribution matrix; if the deviation value of any single battery in the deviation distribution matrix exceeds a preset threshold value, the power battery pack is in an unbalanced state; performing battery state classification on the power battery pack in the unbalanced state, and obtaining an equalization strategy according to a classification result; and according to the equalization strategy control charging system and a preset equalization adjustment priority rule, carrying out equalization charging adjustment operation on the target single battery. According to the invention, the consistency of the battery pack can be improved, the service life is prolonged, the safety risk is reduced, and efficient and intelligent battery management is realized.

The application discloses an intelligent electric chassis configuration and a fault-tolerant control method of the intelligent electric chassis, and relates to the technical field of electric chassis. The chassis configuration comprises a front axle centralized motor drive assembly, a rear axle distributed motor drive assembly, a front axle electronic hydraulic brake system, a rear axle electronic mechanical brake system and a chassis domain controller. The front axle centralized motor drive assembly comprises a centralized drive motor, a front wheel speed reducer and a drive half shaft which are sequentially connected. The rear axle distributed motor drive assembly comprises a left rear wheel end drive motor and a left rear wheel speed reducer which are sequentially connected, and a right rear wheel end drive motor and a right rear wheel speed reducer which are sequentially connected. The front axle electronic hydraulic brake system comprises a first main brake unit and a redundant brake unit. The rear axle electronic mechanical brake system comprises a second main brake unit. The chassis domain controller is used for controlling the centralized drive motor, the left and right rear wheel end drive motors, the first main brake unit, the redundant brake unit, the second main brake unit, a front axle steer-by-wire system, an intelligent suspension system and an intelligent tire. The application can improve the chassis safety and fault-tolerant capability to support high-level automatic driving functions.

This document describes, among other things, a vehicle power system that includes a traction battery, a six-phase inverter divided into two groups of six switches, a six-phase motor, and a pair of switches. In drive mode, the switches configure the inverter to connect the traction battery and the motor. In plug-in mode, the system reconfigures so that one group of switches connects an AC source to the motor, while the other group connects the motor to the traction battery.

Aspects of the present disclosure generally relate to systems and methods for flight control of aircrafts driven by electric propulsion systems and in other types of vehicles. In some embodiments, a system of an aircraft is disclosed, configured to determine one or more desired commands for the aircraft, retrieve engine information for at least one electric propulsion unit (EPU) of a plurality of EPUs of the aircraft, wherein the engine information includes at least one time-based metric for temperature associated with the at least one EPU, generates control commands based on the received engine information, and controls effectors according to the generated control commands to meet the desired commands of the aircraft.

A safety circuit for a high-voltage electrical traction system comprising a plurality of electric machines. The safety circuit comprises a primary high voltage interlock loop (HVIL) circuit configured to be connected to a battery and for each of the plurality of electric machines, a secondary high voltage interlock loop (HVIL) circuit, wherein each secondary HVIL-circuit is controlled by a corresponding switch unit configured to break the secondary HVIL-circuit if a fault in a corresponding electric machine is detected, and wherein the switch unit comprises a trigger device configured to break the primary HVIL-circuit if the switch unit is opened.

The invention relates to a power battery safety protection device of an electric trackless rubber-tyred vehicle, and relates to the technical field of battery safety, the power battery safety protection device is installed on a vehicle body where a power battery is located and comprises a battery rack and a cooling assembly, the battery rack comprises a supporting rack and a sliding rack, the supporting rack is connected to the vehicle body, and the side edge of the supporting rack is warped; the sliding rack is arranged on the supporting rack in a sliding mode, the power battery is installed on the sliding rack, the cooling assembly comprises at least two first spray heads and at least two second spray heads, the first spray heads are located on the two sides of the power battery respectively, and the second spray heads are located at the two ends of the power battery respectively. The first spray head can horizontally swing and vertically swing, the first spray head has two spraying modes of cylindrical spraying and fan-shaped spraying, the spraying range of the first spray head covers the two sides, close to the first spray head, of the power battery, and the spraying range of the second spray head covers the end face of the power battery. The spraying effect of the cooling medium on the power battery is improved.

A battery system includes a cover including a plurality of guide apertures. The battery system includes a thermal barrier disposed adjacent the plurality of guide apertures of the cover. The battery system includes a stiffening structure disposed between the cover and the thermal barrier. The plurality of guide apertures guides emissions through the cover, and the thermal barrier absorbs heat energy generated by the emissions. The battery system may further include a plurality of battery cells, and the thermal barrier may be disposed between the plurality of battery cells and the cover. Each of the plurality of guide apertures of the cover may be aligned with a vent of one of the plurality of battery cells. The stiffening structure may also include cutouts each shaped to correspond to at least one vent. The stiffening structure may also include indentions to press the thermal barrier against the plurality of battery cells.

The invention relates to the technical field of electronics, and discloses a boost circuit control method and device, computer equipment and a storage medium, and the method comprises the steps: detecting a state change event in a boost circuit; calculating a voltage difference value between the front-end voltage value and the rear-end voltage value in the booster circuit, and determining a corresponding target control strategy based on the state change event and the voltage difference value, the target control strategy at least comprises a step of determining a corresponding target voltage value and a feed-forward current value based on vehicle driving parameters and working condition parameters of a load motor so as to execute voltage regulation, or a step of determining a corresponding feed-forward duty ratio based on a rear end voltage value of a booster circuit so as to execute voltage regulation; and executing corresponding control operation on the booster circuit according to the target control strategy. The problems that in the prior art, due to the fact that a control strategy of a booster circuit is fixed, and a state change event and voltage difference value dynamic adjustment are not combined, voltage adjustment response lags behind, and stability is insufficient are solved.

The invention discloses a fuel cell vehicle control method integrating fault diagnosis and energy management. According to the method, vehicle key operation parameters are collected in real time, a whole vehicle operation state vector is constructed, and fuel cell health diagnosis and preliminary power action generation are carried out at the same time based on the state vector. The diagnosis module obtains a health factor and a severity index through residual calculation, particle filtering and generalized likelihood ratio test, and the action generation module outputs an intelligent agent power distribution vector. And according to the severity index, the dynamic reconstruction power, the SOC and the power change rate constraint, optimal power distribution is obtained through optimization solution, and meanwhile, a high-severity state is intervened in combination with a hierarchical fault-tolerant strategy. The method also comprises a demand power prediction and online learning module which is used for improving the robustness and the adaptive capability of the optimization strategy. According to the invention, by tightly combining the health state of the fuel cell with energy management optimization, high-energy-efficiency, long-service-life and reliable dynamic control of the fuel cell system is realized.

The invention discloses a power distribution network cluster local control method and device, equipment and a medium. The method adopts a cloud edge end three-level collaborative architecture, and comprises the following steps: acquiring electrical parameters through a terminal equipment layer; constructing a graph model based on an electrical distance at the edge calculation layer; performing initial cluster division and issuing on the cloud computing layer; dynamically optimizing cluster division in an edge calculation layer through a lightweight deep reinforcement learning model; local control strategies such as voltage reactive power cooperative control, frequency active power balance control and fault rapid isolation and self-healing are executed based on the final division. The system comprises a terminal device layer, an edge computing layer and a cloud computing layer. According to the method, decoupling of global optimization and local real-time control is realized through cloud-side cooperation, the problems of high data processing pressure, high communication delay, expanded local fault influence range and the like of centralized control are effectively solved, and the real-time performance, reliability and disaster resistance of the power distribution network are remarkably improved.

The invention provides a hysteresis coefficient calibration method for a battery, and the method comprises the following steps: discharging the battery from a first initial charge state to a first target charge state through a plurality of unequal discharge currents, and measuring the open-circuit voltage, corresponding to the first target charge state, of the battery after standing for a preset period of time; the measured open-circuit voltage is compared with a reference open-circuit voltage determined according to a reference OCV-SOC corresponding relation to determine a hysteresis coefficient, and the hysteresis coefficient represents the deviation degree of the OCV-SOC corresponding relation of the battery relative to the reference OCV-SOC corresponding relation caused by the hysteresis effect; and determining a corresponding relationship between the discharge currents and the hysteresis coefficients based on the plurality of discharge currents and the corresponding hysteresis coefficients. The present application also proposes a state of charge determination method for a battery, a computer program product, an electronic device, and a vehicle. According to the invention, the state of charge of the battery can be determined more accurately.