25780results about "Electric devices" patented technology

An electric motor based system includes an electric motor; an electric motor power controller for controlling the electric motor; a first control unit, adapted to provide first control signals for the electric motor power controller; an electric power storage device adapted to power the electric motor power controller; a first sensor adapted to determine information related to power exchange between the electric power storage device and the electric motor power controller; and a second control unit, wherein the second control unit is adapted to pass the first control signals, received from the first control unit, to the electric motor power controller in a first mode and adapted to provide second control signals for the electric motor power controller in a second mode; and the second control unit inputs and exploits the information.

The invention relates to the technical field of batteries, and discloses a battery thermal runaway early warning and cooling system which comprises a multi-parameter monitoring module, a data processing and early warning model and a cooling system control module. Wherein the multi-parameter monitoring module is used for acquiring the internal resistance value of each battery monomer in real time in a battery charging process, calculating the internal resistance range, the internal resistance standard deviation and the variable coefficient according to the internal resistance value at a sampling time point, monitoring the working environment gas of the battery through a mass spectrometer, and acquiring the real-time mass spectrum monitoring data of the gas in real time; release characteristics, including hydrogen, hydrocarbon compounds and the like, of escaped gas are quantitatively analyzed on the basis of an equivalent characteristic spectrum method. According to the battery thermal runaway early warning and cooling system, various key parameters in the battery charging process are comprehensively monitored, early warning of the battery thermal runaway risk is achieved, timely intervention is conducted in combination with the cooling system, the thermal runaway risk is reduced, and vehicle and personal safety is guaranteed.

The invention provides a pure electric vehicle charging control method and system, and relates to the technical field of electric vehicle energy storage, and the method comprises the steps: collecting real-time charging data, combining historical data to construct a battery state evaluation model, and calculating battery state information in real time; a multi-objective optimization model is established based on the battery state information, and an optimal charging strategy is solved by adopting an improved particle swarm algorithm; and a multi-dimensional safety monitoring system is established, a corresponding safety plan is executed when abnormal charging is detected, and the plan is fed back to the multi-target optimization model for strategy correction.

A system (100) for intelligent fault detection and energy management in fuel cell hybrid electric vehicles (FCHEVs), comprising: a data acquisition unit (102) comprising sensors (102a) configured to acquire real-time operational data from vehicle components; an energy management unit (104) comprising a fuel cell unit configured to generate electricity from hydrogen and a battery unit configured to store and supply electrical energy; a regenerative braking system (106) in conjunction with an energy management unit (104) configured to recover and store energy during vehicle deceleration; a centralized processing unit (108) configured to perform functions of the system (100) based on data acquired by the sensors (102a), wherein the centralized processing unit (108) comprises the following: a neural network processor (108a) configured to analyze real-time operational data for fault prediction; an energy optimization processor (108b) configured to dynamically manage power distribution; a maintenance prediction processor (108c) configured to identify potential component failures; a communication interface (110) configured to enable data exchange between vehicle and infrastructure (V2I) and between vehicles (V2V); a driver interface (112) configured to display system status and receive user input; and a control unit (114) configured to perform corrective actions based on neural network analysis and energy optimization calculations.

A robotic device comprising internal and external sensors is physically coupled to or hosts a controllable device such as a computer interface device. Based on inferences the robotic device controls a controllable device user interface via at least one actuated link. Multiple robotic devices may be coupled and composed to host and manipulate multiple controlled devices.

A battery containment construct is provided that includes a unitary tray having a bottom and a set of walls including a first side wall, a second side wall, a first end wall, and a second end wall. The set of walls extending from the bottom of the tray and defining a cavity within the tray. A cover removably attached to the plurality of walls of said tray opposite the bottom of said tray. Energy absorption components attached to the bottom of the tray external to at least one of the set of walls in some versions to enhance impact resistance. The construct has high strength, is light weight and well suited for containing and protecting energy cells or batteries that adjusted to impact resistance, fire resistance, and fluid penetration prevention.

The invention provides an electric motorcycle charging control method based on battery electric quantity, which comprises the following steps: when an electric motorcycle is charged, acquiring inclination angle data of a side bracket of the electric motorcycle, if the inclination angle is within a preset range, judging that a motorcycle body is in an inclination state in a charging state, and triggering a monitoring program of a battery pack cooling liquid flowing state; temperature data of the identified single batteries in the non-uniform cooling liquid distribution area are collected in real time through a temperature sensor array, gradient analysis is carried out on the temperature data, the position and severity of a thermal unbalance fault are determined, and data support is provided for subsequent charging strategy adjustment and cooling system optimization; the temperature distribution and the flow track of the cooling liquid at different inclination angles are simulated, and the heat dissipation risk area at the current inclination angle is determined by comparing and analyzing the uniformity of the temperature distribution and the smoothness of the flow.

The present disclosure generally relates to a battery pack for an electric vehicle. In some implementation examples, the battery pack has an array of battery cells and a battery pack enclosure for holding the array of battery cells. The battery pack enclosure has a top surface above the array of battery cells. An impact attenuation layer can be integrated into at least a portion of the top surface of the battery pack enclosure. The impact attenuation layer has a first sub-layer and a second sub-layer. The first sub-layer has a first puncture resistance attribute and a first impact resistance attribute and the second sub-layer has a second puncture resistance attribute and a second impact resistance attribute. The first puncture resistance attribute is higher than the second, puncture resistance attribute and the first impact resistance attribute is lower than the second impact resistance attribute.

To enable detection of temperature rise of electronic equipment disposed in a battery pack due to radiation heat in an exhaust passage.SOLUTION: A battery pack 50 disposed on the underfloor of a hybrid vehicle 1 includes: a battery stuck 55 where battery cells are laminated; a battery ECU51 and a monitoring unit 52. A temperature sensor 53 fitted to a flue gas passage 94 is disposed at a position between the battery ECU51 and the monitoring unit 52, and an exhaust pipe 21. The temperature sensor 53 is disposed between the battery ECU51 and the monitoring unit 52, and the exhaust pipe 21, and therefore favorably detects the temperature rise of the battery ECU 51 and the monitoring unit 52 due to radiation heat from the exhaust pipe 21.SELECTED DRAWING: Figure 2

A method of repairing a used battery pack from an electric vehicle include removing the battery pack from the vehicle. Battery tests are performed on at least some of the plurality of batteries and a battery test result for each of the batteries tested are obtained and stored in a database. A plurality of replacement batteries are tested and test results for each of the replacement batteries are stored in the database. The battery test results from the database are retrieved and used to create a refurbished battery pack. An apparatus includes a database for storing test results.

The invention relates to the technical field of intelligent control of transformer substations, in particular to a standardized intelligent control system of a transformer substation, which realizes real-time response to the running state of equipment by acquiring the current, voltage, power factor, temperature and humidity, operation state, insulation state and environment temperature and humidity of a power transformation unit in real time. A gradient boosting decision tree is combined with a variational auto-encoder and a self-attention mechanism, state vector features are extracted, complex abnormal states are accurately recognized, potential faults are detected in an early stage, and the monitoring efficiency and the early warning precision are greatly improved. The future power demand is accurately predicted by combining the long-short-term memory network model with historical and real-time load data, and the limitation of traditional static load management is overcome. Based on the predicted power demand, the reinforcement learning model is adopted to dynamically adjust the operation number of the power transformation units, optimal configuration of resources is achieved while the demand is met, and the overall operation efficiency of the transformer substation is remarkably improved.

An electrified fire fighting vehicle includes a chassis, a front axle coupled to the chassis, a rear axle coupled to the chassis, a water pump, an energy storage system, an engine, an electric motor coupled to the engine and the energy storage system, and a power divider positioned between the electric motor, the water pump, and the rear axle. The power divider facilitates selectively driving the water pump and the rear axle with the engine and the electric motor.

A method for manufacturing an electric vehicle battery case includes: preparing a frame configured to define a through space inside and a flat plate made of resin; superposing and disposing the flat plate on the frame; and applying pressure to the flat plate from an opposite side from the frame to press the flat plate against the frame to cause the flat plate to swell in the through space, thereby deforming the flat plate into a tray having a bathtub shape including a bottom wall and a peripheral wall provided at a peripheral edge of the bottom wall and configured to define an opening portion, and joining by press-fitting the tray to the frame.

A vehicle includes a chassis including a frame rail extending longitudinally, a tractive element coupled to the chassis, a cab coupled to the chassis and configured to support an operator, an electric motor configured to drive the tractive element to propel the vehicle, a battery configured to supply electrical energy to the electric motor, a heat exchanger, a cable electrically coupling the electric motor and the battery, and a conduit fluidly coupling the battery and the heat exchanger. The cable and the conduit extend laterally from the battery to the frame rail, and the cable and the conduit extend longitudinally along the frame rail.

Examples relate to vehicle battery systems comprising a base unit connectable to a vehicle's electrical system, a removable modular replaceable battery, and a secondary battery within the base unit. The base unit is configured to interchangeably use modular replaceable batteries of different chemistries. Control circuits optimize charging and discharging parameters based on battery chemistries. The secondary battery provides power when the modular battery is removed. The system includes thermal management, compatibility with lead-acid charging systems, and mobile base unit functionality. The modular battery can power external devices and can foreseeably store energy up to and beyond 1 kWh. The system operates at various voltages suitable for different vehicle types.

The invention discloses a system for monitoring line loss rate abnormity of a power distribution network station area, and relates to the technical field of power distribution network monitoring. The line loss rate abnormity monitoring system for the power distribution network station area comprises a data acquisition module, a data processing module, a line loss rate calculation module, an abnormity identification and alarm module and an on-site troubleshooting and diagnosis module. Through integrating functions of intelligent electric meter data acquisition, power grid data collection and area division, data processing, line loss rate calculation, abnormity identification and alarm, on-site troubleshooting and diagnosis and the like, comprehensive and real-time monitoring of the line loss rate of the power distribution network station area is realized. And a regional line loss calculation model is established according to the characteristics of the power distribution network of each region, and the line loss rate can be monitored in real time, dynamically calculated and predicted, so that the efficiency and accuracy of line loss management are greatly improved. And the abnormity identification and alarm module can timely discover and give an alarm of line loss abnormity, provides probability analysis of abnormity reasons, and is helpful for operation and maintenance personnel to quickly respond and process.

The present disclosure relates generally to flight control of electric aircraft and other powered aerial vehicles. In one embodiment, a method is disclosed, comprising: receiving a descent rate command from a pilot input device, determining a proximity of each propeller of at least two propellers to a vortex ring state; and controlling the aircraft's descent rate to be less than the commanded descent rate when at least one of the at least two propellers is within a first threshold proximity to the vortex ring state.

The invention provides a system design method and system supporting automatic testing of multiple radio frequency parameters, and relates to the technical field of testing, and the method comprises the steps: receiving and analyzing a test task, generating a test configuration file according to the information of radio frequency equipment to be tested and multiple radio frequency parameter test items, and using a self-adaptive optimization algorithm to optimize the test configuration file. Dynamically adjusting the test configuration file based on historical test data to generate an optimized test configuration file; controlling a radio frequency signal generator to generate a test signal, inputting the test signal into the radio frequency equipment to be tested, starting a real-time monitoring module, performing multi-dimensional analysis on a digital signal processed by a radio frequency signal analyzer, performing anomaly detection on an analysis result by using a deep learning algorithm, identifying and marking an abnormal data point; and generating a test report according to the analysis result and the anomaly detection result.

The invention relates to the technical field of battery capacity prediction, and discloses a golf cart battery capacity prediction method, device and equipment and a storage medium, and the method comprises the steps: carrying out the collection and preprocessing of historical charging and discharging data of a golf cart battery, and obtaining a time sequence feature data set; generating an incremental capacity curve, inputting the incremental capacity curve into a bidirectional long-short-term memory network, and training to obtain an initial capacity prediction model; taking the initial capacity prediction model as a first-layer model, and taking the metabolism grey model as a second-layer model for stacking and integrating to obtain a mixed prediction model; dynamically adjusting model parameters through a double-layer optimization algorithm to obtain a target capacity prediction model; and inputting real-time battery operation data into the target capacity prediction model to carry out capacity prediction and health state evaluation, and outputting a capacity attenuation trend chart and a residual service life estimation value, so that the precision of predicting the battery capacity of the golf cart is improved.

An apparatus and method relate to analyzing metrics relating to EV charging points and facilitating selection of an EV charge point based on metrics associated with the EV charge points. Methods may include: determining locations of one or more electric vehicle charging stations; determining a total power available at the one or more electric vehicle charging stations; determining, for the one or more electric vehicle charging stations, if dynamic load balancing is used; determining occupancy of charge points at each of the one or more electric vehicle charging stations; calculating an available power at a charge point of the one or more electric vehicle charging stations based on the total power available and the occupancy of charge points for the one or more electric vehicle charging stations; and calculating an estimated time to charge a vehicle at the one or more electric vehicle charging stations based on the available power.

A Level IV fuel-saving robot system for ACE HDTs of the present disclosure focuses on the minimization of actual fuel consumption (L / 100 km) for long-haul freight at first based on an electrical power split device (ePSD) and a mixed hybrid powertrain architecture. A basic model Level I fuel-saving robot realizes a longitudinal L1 automatic driving function through a predictive adaptive cruise (PACC) technology within an Operational Design Domain (ODD) for highways and reduces the actual fuel consumption of an ACE HDT by more than 20% compared with modern diesel HDTs, and the energy-saving and emission-reducing effect of the basic model Level I fuel-saving robot is decoupled from both the technical level of a vehicle engine and the driving level of a driver; an advanced Level IV fuel-saving robot has a L4 automatic driving function within the ODD for highways, operates in a “shadow mode” or “detached mode”, automatically generates a discrepancy report or detachment report, completes the “3R” batch validation for an L4 system on a billion mile scale quickly with high cost effectiveness on the premise of ensuring the traffic safety of existing road users and reduces the total validation expense by more than 65% compared with the modern HDT with internal combustion engine equipped with the L4 system, promoting the early commercialization of the Level IV fuel-saving robot.

The invention discloses an intelligent diagnosis system of a power distribution network fault self-judgment switch device, and relates to the technical field of power system automation and intelligent power grids, and the intelligent diagnosis system comprises an intelligent diagnosis system interconnection hub which is in communication connection with a power parameter monitoring module, an intelligent fault detection module and a visual decision support module; the electric power parameter monitoring module monitors the state of a power distribution network in real time through a mutual inductor, voltage, current, power factors and harmonic data are collected through an intelligent electric meter, the intelligent fault detection module achieves fault recognition, trend prediction and anomaly detection through an LSTM neural network, and the decision support module provides a graphical interface and automatically generates a fault response strategy. According to the method, autonomous judgment and quick response of the power distribution network fault are achieved, the accuracy and efficiency of fault detection are remarkably improved, the false alarm rate and the missing report rate are reduced, meanwhile, the decision support module of the graphical interface simplifies the fault processing flow, and the stability and safety of power grid operation are improved.

A system for controlling a vehicle, includes: a central controller and multiple vehicle components. The vehicle components correspond to multiple functional domains, and at least one vehicle component in each of the functional domains is connected to the central controller. The central controller is configured to send first control information to the at least one vehicle component. The functional domains includes a power domain. A vehicle component in the power domain includes a motor controller and multiple drive motors corresponding to wheels and respectively driving the wheels. The first control information includes torque allocation information of each of the drive motors. The central controller is configured to send the torque allocation information to the motor controller according to a vehicle driving scenario.

The invention provides an energy consumption prediction and anomaly detection method and system based on digital twinning, and the method comprises the steps: collecting physical parameters in real time through a sensor, and the physical parameters comprise the cell temperature, the total current of a battery pack, the total voltage of the battery pack, the gradient, the vehicle speed and the mass; collecting battery state parameters by using a battery management system, wherein the battery state parameters comprise real-time energy consumption; the collected physical parameters are input into a Simulink and Cruise combined model for simulation, and model output prediction energy consumption is obtained; wherein the Simulink is used for establishing an equivalent circuit model of a power battery, and the control system, the sensor simulation module and the Cruise simulation model are used for establishing a whole-vehicle simulation model of the pure electric vehicle; comparing the model output energy consumption with the real-time energy consumption, and obtaining an energy consumption deviation value; whether the energy consumption deviation value exceeds a preset range or not is judged, and if yes, energy consumption is judged to be abnormal; and if not, evaluating the energy consumption of the whole vehicle so as to solve the technical problem that the actual energy consumption analysis, energy management and endurance mileage evaluation of the whole vehicle are difficult.

The invention discloses an inverter intelligent control method based on a self-adaptive algorithm, and relates to the technical field of inverter intelligent control, and the method comprises the steps: multi-source temperature collection and environment recognition, machine learning-based electric-thermal coupling prediction, self-adaptive inverter parameter optimization, and cooperative thermal management and fault diagnosis self-repairing. According to the high-temperature or low-temperature failure risk of the motor and the inverter under the extreme climate, temperature distribution and load information are obtained in real time, the temperature rise trend is predicted in advance, and the current, voltage and modulation strategy of the inverter are actively adjusted, so that safe derating or torque compensation is achieved; multi-sensor cross validation and observer fusion are carried out when sensors drift or devices are aged, stable operation and efficient energy utilization of the system are kept, and the drivability and the whole vehicle reliability in an extreme environment are remarkably improved; in the process, fault diagnosis and self-repairing can be further improved through online model updating, and the durability and economical efficiency of the electric drive system are improved.

The invention relates to the technical field of battery power supply fault detection, and particularly discloses a power supply fault detection method and system for an electric vehicle battery, and the method comprises the steps: collecting the multi-modal data of the electric vehicle battery, carrying out the preprocessing and feature extraction of the multi-modal data of the electric vehicle battery, and constructing an intelligent diagnosis model. And carrying out potential fault propagation path prediction, predicting the diffusion path and speed of the fault in a battery system, carrying out electric vehicle battery fault positioning and early warning, and outputting a three-dimensional power supply fault thermodynamic diagram and a hierarchical autonomous disposal instruction of the electric vehicle battery. According to the invention, the problems of poor detection effect, emphasis on single fault diagnosis, large diagnosis difficulty, influenced accuracy and the like caused by incapability of accurately adapting to a fault detection method based on a model in a complex and changeable actual working condition in the prior art are solved.

The present invention is directed to electronic devices, systems, and methods for optimizing dispatch schedules for an electric vehicle battery in communication with the electronic device to maximize the revenue generation from vehicle-to-grid activities at a site while also preserving battery health. The devices, systems, and methods may determine, using an optimization algorithm, the dispatch schedule for the electric vehicle battery and control a charge or discharge of the electric vehicle battery based on the dispatch schedule. The optimization algorithm may determine the dispatch schedule based on forecasts for future anticipated energy needs of the site and forecasts for future anticipated energy production of the site. The optimization algorithm may include an objective function including one or more variables. The devices, systems, and methods may introduce a heuristic term to the objective function or penalize the first derivative of a variable of the objective function to optimize the dispatch schedule.

The invention discloses a power distribution system and method for a modular power supply, and aims to optimize power distribution through an intelligent means, improve the operation efficiency and stability of the system, and control a unit to check the states of all power supply modules, and evaluate the required total power output according to the load demand. Then, based on the capability of each module and a redundancy planning principle, an appropriate module combination is selected to meet the load requirement, and necessary voltage or current adjustment is carried out to ensure stable power supply. In the operation process, the control system continuously monitors the state and the overall performance of each module, and once a fault or an abnormal condition is detected, measures such as automatic switching to a standby module are taken immediately, so that the continuity and the safety of the system are ensured. In addition, through analysis and learning of historical data, the system can continuously optimize a power distribution strategy, and efficiency and reliability are further improved. And the ability of the system to deal with emergency situations is also enhanced.

The invention discloses a vehicle stopping electrical safety monitoring system, and relates to the technical field of new energy vehicle control, the vehicle stopping electrical safety monitoring system comprises an intelligent sensing layer, a digital twin decision-making layer, a hierarchical execution layer and a safety escape layer, and the intelligent sensing layer comprises a multi-mode sensor array and is used for collecting physical parameters, chemical parameters and environmental parameters of a vehicle electrical system in real time. According to the method, a high-precision three-dimensional model, an embedded electrolyte leakage model and a wire harness aging model are constructed, the high-precision three-dimensional model comprises a battery compartment geometric structure and a wire harness layout, the former simulates a diffusion path and predicts a short-circuit risk based on fluid dynamics, and the latter realizes fault evolution prediction based on a physical mechanism by combining vibration fatigue and insulation material aging analysis. The hysteresis of traditional threshold value alarm is broken through, a dynamic threshold value table is generated in combination with environment temperature, the charge state and historical fault data, the problem that a traditional fixed threshold value cannot adapt to complex working conditions is solved, and the false alarm rate and the missing alarm rate are reduced.

The invention discloses a new energy automobile charging control method and system combined with battery health monitoring, and relates to the technical field of charging control, and the method comprises the steps: collecting the working state of a target battery, and carrying out the health assessment; extracting a battery sample, positioning a health stage, and generating a life cycle position; performing progressive charging control on the target battery to obtain charging parameters; health assessment, decline analysis and stage division are carried out, and a predicted life cycle position is generated; and carrying out preamble judgment on a life cycle position, and analyzing preamble influence factors to generate a maintenance suggestion. The technical problems that in the prior art, the battery state cannot be comprehensively monitored and managed, so that the charging potential safety hazard of the battery is high, and the service life is short are solved, the full-process management from state collection, health assessment and charging control to fault prediction and maintenance suggestion generation of the battery is achieved, and the management efficiency of the battery is improved. The charging safety of the battery is improved; and the overall service life of the battery is prolonged.