855 results about "Charge rate" patented technology

A smart ring charging system comprises a charging source integrated into an object, the object configured to be held by a user wearing a smart ring. The smart ring may include a ring-shaped housing and a power source disposed within or at the ring-shaped housing and configured to receive energy from the charging source while the user is wearing the smart ring and holding the object. A controller may be disposed within or at the ring-shaped housing, or at the object with the charger and configured to estimate a charging rate at which the power source receives the energy from the charging source. The system may further include one or more indicators configured to indicate the charging rate.

A power tool battery charger includes a housing, at least one charging circuit coupled to the housing, and an electronic controller coupled to the housing. The electronic controller is configured to receive power tool device data from a power tool device, which may be the same or another power tool battery charger, a battery pack, and / or a power tool. The power tool device data indicate various data associated with the power tool device. Charger operation data are generated by the electronic controller based on the power tool device data, and can include a charging rate, charging target, and / or time indication for when to adjust the charging rate and / or charging target of the at least one charging circuit. A machine learning or artificial intelligence controller can also be used when generating the charger operation data. The at least one charging circuit is then operated based on the charger operation data. Alternatively the above functions can be provided by a battery pack for use with a power tool, the battery pack comprising a charging circuit.

Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a base station, a first physical downlink shared channel (PDSCH) transmission transmitted using a first modulation and coding scheme (MCS). The UE may transmit, to the base station, feedback based at least in part on decoding the first PDSCH transmission, wherein the feedback includes an acknowledgement (ACK) or negative acknowledgement (NACK) and a channel state information (CSI) report that includes at least an indication of a second MCS based at least in part on a target block error rate (BLER) and a target charging rate for energy harvesting. Numerous other aspects are described.

The invention discloses a charging pile self-adaptive charging planning method based on data mining, and relates to the technical field of self-adaptive charging, and the method comprises the steps: carrying out the real-time data collection and load prediction, dynamically adjusting a charging strategy, intelligently distributing charging resources in a peak load period, limiting high-power charging, and avoiding the overload of a power grid; in the idle load period, the idle capacity of the power grid is fully utilized, the power grid load is balanced, and the stability and safety of the power grid are guaranteed; through behavior data analysis and user portrait construction, users are divided into a high-priority type and a low-priority type, the charging rate and resource allocation are flexibly adjusted according to the requirements of different users, the high-priority users can obtain faster charging services, the low-priority users can enjoy more economical charging options, resource waste is avoided, and the user experience is improved. And meanwhile, the overall satisfaction degree of the user is improved.

The present disclosure relates to a battery lithium plating detection method and apparatus, and a device, a vehicle, a medium and a program product. The method comprises: determining the actual direct-current internal resistance of a battery in each charge sub-stage during step charge, wherein the step charge comprises at least two charge sub-stages, and the battery is charged at a target charge rate and a constant current in each charge sub-stage; determining the target direct-current internal resistance of the battery in a corresponding charge sub-stage, wherein the target direct-current internal resistance is a predicted value of direct-current internal resistance that is obtained by means of a preset mathematical model; and if the difference value between the actual direct-current internal resistance and the target direct-current internal resistance is greater than a preset difference threshold value, determining that the battery is in a lithium plating state.

The invention relates to the technical field of current compensation, and discloses a current compensation strategy and a compensation system for improving the direct current fast charging rate of an electric automobile. According to the scheme, the total current of a high-voltage loop and the input current of a battery are detected in real time, the dynamic load current difference value is calculated, and the battery health state and historical charging data are combined; and the charging pile request current value is adaptively adjusted to counteract the shunting influence of the load power. Meanwhile, a closed-loop feedback regulation mechanism is adopted, a compensation coefficient is corrected in real time through a PID algorithm, and the stability of the charging current is ensured. When the power of the charging pile is limited, the system dynamically reduces unnecessary loads (such as an air conditioner and a heater) according to a preset priority request, and the charging power of the battery is guaranteed preferentially. The charging rate is improved (the charging time is shortened by 10%-15%), the adaptability of the system to dynamic load fluctuation is enhanced, and the service life of the battery is prolonged.

The invention provides a new energy storage optimization system and method, a storage medium and electronic equipment, and relates to the technical field of new energy. The system comprises an energy storage equipment state evaluation module which is used for obtaining real-time operation data of energy storage equipment and evaluating the health state of the energy storage equipment in combination with historical charging and discharging data of the energy storage equipment; the power grid load demand prediction module is used for determining a target power grid load demand through a trained load prediction model based on the power grid load data and the external environment data; and the energy storage equipment scheduling optimization module is used for determining charging and discharging adjustment parameters of the energy storage equipment by utilizing a scheduling optimization model based on the health state of the energy storage equipment and the target power grid load demand, and adjusting the charging rate and the discharging power of the energy storage equipment according to the charging and discharging adjustment parameters. According to the invention, dynamic optimization scheduling is carried out on the energy storage equipment, so that the service life of the energy storage equipment can be prolonged, the energy utilization efficiency of the energy storage system is improved, and the stability of the energy storage system is improved.

Some techniques described herein provide indication of a preferred scheduling mode for a user equipment (UE) based at least in part on an energy harvesting state of the UE. For example, the preferred scheduling mode may indicate a configured grant scheduling mode or a dynamic grant scheduling mode and / or one or more parameters associated with the preferred scheduling mode. For example, the one or more parameters may be based at least in part on an energy harvesting state of the UE. By indicating the preferred scheduling mode, the UE can selectively perform a transmission using a dynamic grant resource or a configured grant resource. Thus, the UE can request a dynamic grant resource when the UE is associated with a high energy level or a relatively fast charging rate, or a CG resource when the UE is associated with a low energy level ora relatively slow charging rate.

The invention discloses a health state prediction analysis method and system based on a charging pile, and relates to the technical field of charging pile management, and the method comprises the steps: carrying out the data extraction processing of a database system based on a central processing unit, and obtaining the historical operation data of the charging pile; and obtaining complete historical operation data of the charging pile. According to the method, whether the state of the charging pile is the healthy state or not is determined by judging the temperature deviation value of the charging pile, the charging deviation value of the charging pile and the factory parameter information of the charging pile, in addition, the state of the charging pile in the healthy state is predicted, and the state of the charging pile in the healthy state can become sub-healthy within the time. The state of the charging pile is monitored, damage to internal electronic components of the charging pile due to too fast temperature rise of the charging pile is avoided, the service life of the charging pile is prolonged, the charging speed of the charging pile is monitored, abnormal energy loss caused by too long charging time of the charging pile is avoided, and the charging cost is reduced.

In one aspect, a computer-implemented method for executing an artificial intelligence (AI) engine, including executing a categorization model configured to categorize, into categories, vehicles based on factors comprising age, temperature conditions, usage patterns, battery health metrics, or some combination thereof, executing a behavior analysis model configured to analyze behavior of the vehicles in each of the categories to identify battery performance metrics including charging habits, discharge rates, charge rates, state of charge, state of health, state of power, or some combination thereof, executing a recommendation generation model configured to generate, based on the battery performance metrics, recommendations for enhancing battery management strategies, wherein the recommendation generation model accounts for a current state of a vehicle to suggest actions to improve battery health; and executing a battery model configured to determine power and energy consumption based on the recommendations generated by the recommendation generation model.

The invention discloses a low-temperature slow charging control method and device and a vehicle, and relates to the technical field of battery charging, and the low-temperature slow charging control method comprises the steps that temperature rise data of a battery pack is acquired; based on the temperature rise data of the battery pack, obtaining available charging power of the battery pack; determining a power distribution point based on the charging available power; and based on the power distribution point, distributing the power for charging the battery pack by the charging pile. According to the temperature rise data of the battery pack, the heating power required by the battery pack in the low-temperature environment is obtained; and in combination with the maximum power capable of being provided by the charging pile, the available charging power of the battery pack is obtained. And based on the available charging power of the battery pack and the maximum acceptable charging power of the battery pack, comprehensively considering the heating demand and bearing capacity of the battery pack, and confirming a power distribution point. The power distribution point can realize the distribution of the heating power and the charging power which utilize energy to the maximum extent, improve the charging rate and solve the distribution problem.

The present disclosure provides a self-adaptive lithium-ion battery method using knowledge-reinforced machine learning and Kalman filtering, an electronic device, and a storage medium. The method includes training and synchronizing an artificial neural network with dual extended Kalman filters to capture battery capacity data of each of lithium-ion batteries; integrating prior knowledge with Gaussian process regression to form an integrated knowledge-reinforced Gaussian process regression; training a stochastic capacity degradation model by employing integrated knowledge-reinforced Gaussian process regression with captured battery capacity data to obtain a trained stochastic capacity degradation model; performing capacity prediction using trained stochastic capacity degradation model to obtain remaining useful life of one or more testing lithium-ion batteries; generating an air mass flow rate and a charging / discharging rate by a controller; and inputting the air mass flow rate and the charging / discharging rate into a battery thermal management system to improve battery RULs by adjusting lithium-ion battery temperature.

The invention relates to the technical field of charging infrastructure management, and particularly discloses a charging pile appointment scheduling and path planning cooperation system and a charging pile appointment scheduling and path planning cooperation method. According to the method, continuous wavelet transform and fast Fourier transform are adopted to extract a charging rate fluctuation characteristic value and a power grid power supply stability characteristic value for quantitatively evaluating the service stability of a charging pile and the power supply reliability of a regional power grid, and the system fuses the characteristic values into a comprehensive characteristic vector as the input of a gradient boosting tree model so as to obtain a gradient boosting tree model; and training the prediction model to output a charging planning score so as to judge whether the user can smoothly complete the charging task, and if a prediction result does not meet a set threshold value, dynamically adjusting a reservation scheduling strategy and re-planning an optimal charging path.

The present invention discloses a formation method for a sodium-ion single battery, which includes constant current charging of the sodium-ion single battery at a charging rate of 0.1C - 0.5C under the condition of 20 - 25°C, and the charging cut-off voltage is V C1 and standing still for 30 - 60 minutes, placing the single battery under the condition of 2 - 10°C for 1 - 2 h, and using voltage V C2 to perform constant voltage charging for 2 - 5 seconds and then standing still for 3 - 8 seconds, standing still for 30 - 60 minutes under the condition of 20 - 25°C, and performing constant current discharging of the sodium-ion single battery at a discharging rate of 0.1C - 0.5C, and the discharging cut-off voltage is V D1、 placing the single battery under the condition of 35 - 55°C for 1 - 2 h, and using voltage V D2 to perform constant voltage discharging for 3 - 6 seconds and standing still for 5 - 8 seconds. The formation method of the sodium-ion single battery significantly changes the performance of the sodium-ion battery, effectively improving the first capacity, charge and discharge efficiency, and cycle life of the sodium-ion battery.

A method for charging a rechargeable lithium-ion battery in an aerosol-generating system is provided, the method including: initiating charging of the rechargeable lithium-ion battery; monitoring an electrical parameter indicative of a charging rate of the rechargeable lithium-ion battery; determining the charging rate of the rechargeable lithium-ion battery by monitoring a change of the electrical parameter over a given time period; and comparing the determined charging rate to a reference charging rate, the reference charging rate being defined by an expected change in the monitored electrical parameter; and if the charging rate deviates from the reference charging rate, inhibiting the rechargeable lithium-ion battery from being charged. A charge controller for an aerosol generating system is also provided. An aerosol-generating device is also provided. A charging case for an aerosol generating device is also provided.

The application discloses a kind of fast charging method and device of lithium ion battery, it is related to power battery charge-discharge technical field.The application aims at the problem that the fast charging method of existing lithium battery cannot better adapt to the state of lithium battery in different charging stages.The SOC interval is selected in the application, and the SOC interval is divided into several charging stages with the defined ΔSOC as interval;The residual life prediction value of lithium ion battery is obtained according to the temperature, state of charge, charge rate and charge cycle number of lithium ion battery;The characteristic curve of lithium ion battery is obtained, and the charge time weight α of each charging stage is obtained according to the charge characteristic curve;The charging current of each charging stage is obtained by inputting the charging time, charge time weight and residual life prediction value into target equation.The application effectively prolongs the service life of battery while ensuring safe and fast charging.

The invention relates to the technical field of charging pile charging control, is used for solving the problem of damage to a rechargeable battery caused by unreasonable charging of a charging pile, and particularly relates to a charging pile charging control method based on communication supervision. According to the invention, analysis is carried out from two points of the actual charging performance of the target charging pile and the state risk of the rechargeable battery, so that the target charging pile is managed reasonably and specifically according to the information feedback condition, and the charging stability of the target charging pile and the charging safety of the rechargeable battery are ensured; and charging adjustment feedback analysis is performed on the basic data in a progressive manner, so that the charging power of the target charging pile is reasonably adjusted according to the information feedback condition, the charging risk in the charging process of the rechargeable battery is reduced, analysis is performed from the angle of the charging rate, and the charging efficiency is improved. Therefore, the target charging pile can be managed according to the feedback condition, the healthy operation of the target charging pile can be improved, and the damage of the target charging pile to the rechargeable battery can be reduced.

The invention provides a charging control method and device for a battery changing cabinet, electronic equipment and a storage medium, and the method comprises the steps: obtaining the environment information of the environment where the battery changing cabinet is located in a preset time period, and determining the severe grade of the environment where the battery changing cabinet is located based on the environment information; determining that the severity level is smaller than a preset level threshold; and obtaining cabinet body temperature information of the battery replacement cabinet and battery temperature information of the batteries in the battery replacement cabinet, and performing hierarchical control on the charging rate of the batteries in the battery replacement cabinet based on the cabinet body temperature information and the battery temperature information. Charging of the batteries in the battery changing cabinet is controlled through the environment information, the cabinet body temperature information of the battery changing cabinet and the battery temperature information of the batteries in the battery changing cabinet, the spontaneous combustion risk of the battery changing cabinet and the batteries caused by climate factors is reduced, it is ensured that the batteries can achieve reasonable charging rates under various environment conditions, and the charging efficiency of the batteries is improved. Therefore, the service life of the battery changing cabinet and the battery is effectively prolonged, and the overall safety and reliability are further improved.

The utility model discloses an electrode plate and a lithium ion battery. The electrode plate comprises a current collector, a positive electrode and a negative electrode, the edges of the two sides of the current collector are coated with the functional coatings; the active material coating is coated on at least one surface of the current collector and covers the functional coating; the ratio of the thickness of the functional coating to the thickness of the current collector is 0.2-1, and the functional coating is used for weakening lithium ion transmission. According to the invention, the balance between the conductivity of the coating and the lithium removal capacity of the active substance is maintained by adjusting the parameters of the coating, that is, the lithium ion de-intercalation speed is controlled by optimizing the structure and parameters of the pole piece coating, so that the capacity of improving the charging rate of the battery cell is achieved.

The invention discloses a lithium ion battery charging method, a control system and a storage medium, and the charging method comprises the steps: carrying out the multi-stage charging according to a plurality of divided SOC intervals, and carrying out the constant-current charging of each SOC interval through employing different charging rates. The plurality of SOC intervals are divided according to a peak value or an inflection point of a differential voltage curve calculated by a charge-discharge test of the target battery; the charging rate adopted by each SOC interval is calculated through the following formula: n is the target total charging time, and the unit is h; i and j represent the i or j SOC interval; m is the number of the divided SOC intervals; rj is the percentage of the j-th SOC interval needing to be charged; d is the negative electrode solid phase diffusion coefficient of the corresponding SOC interval. A lithium intercalation reaction stage is identified by analyzing a differential voltage curve, and key kinetic parameters are tested, so that an internal kinetic limit is finally converted into an external executable charging rate, and safe and efficient rapid charging is realized.

The charging management system based on variable charging windows is disclosed. The system can receive and / or determine an anticipated / desired time for the beginning operation of the vehicle. The system obtains or identifies preferences for charging metrics, including desired charge, battery pack preconditioning, and other vehicle attributes. The system then determines a required start time for the desired charging metrics. Illustratively, the determined start time can be based on ambient environmental conditions that can influence charging times, such as differences in charging times based on temperature. The determined start time can also be based on rate schedules for one or more power sources, such as one or more off-peak charging rates, peak charging rates, etc.

Systems and methods for determining a total chargeable / dischargeable energy of a subsystem of a battery energy storage system (BESS) are disclosed. An iterative process is executed over a dynamic time period divided into iterations using a neural network model comprising an energy prediction sub-model and a state prediction sub-model. The energy prediction sub-model outputs a chargeable / dischargeable energy of the subsystem for the current iteration. The state prediction sub-model outputs a voltage of the subsystem for a next iteration, the charge rate of the subsystem for the next iteration, the maximum temperature of the subsystem for the next iteration, and a charge rate difference for the next iteration. A total chargeable / dischargeable energy of the BESS subsystem is determined by summing the dischargeable energies determined for each iteration.

A battery control device that controls a battery pack in which a plurality of batteries are connected to each other detects a voltage variation between the plurality of batteries, calculates a restriction coefficient based on a charging rate of the battery pack and the voltage variation, and restricts inputtable / outputtable power based on the restriction coefficient, the inputtable / outputtable power being maximum power inputtable to and outputtable from the battery pack.

A charging method, including: obtaining the number of charge-discharge cycles of a battery and an application scenario during charging; determining a target charging mode among at least two charging modes according to the number of charge-discharge cycles and the application scenario, in which different charging modes have different charging rates, and the charging modes with different charging rates have different charging damages to the battery; and charging the battery in the target charging mode.

A method for charging a battery includes: determining a first charging section, in which a current charging rate of the battery is located, from among a plurality of charging sections predetermined based on a functional relation between a state of charge of the battery and an open circuit voltage of an anode of the battery; and charging the battery for the first charging section with a first charging rate corresponding to the first charging section.

An electric vehicle includes a system for charging a battery of the electric vehicle. The system includes a sensor for obtaining a reference measurement of the battery during charging and a processor. The processor is configured to calculate an augmented state from the reference measurement, determine an anode voltage from the augmented state, compare the anode voltage to a threshold, and adjust a charging rate based on the comparison of the anode voltage to the threshold.

The invention provides a display device and a display method. The display device comprises a display panel and a driving chip, the driving chip comprises a voltage regulating unit, an overvoltage driving unit and a triggering unit; the trigger unit is used for detecting whether the current display picture of the display panel is a heavy-load picture or not, and when the display picture is the heavy-load picture, the trigger voltage regulation unit and the overvoltage driving unit are triggered to work cooperatively; the voltage adjusting unit is used for adjusting a target driving voltage corresponding to a target gray scale in the liquid crystal driving voltmeter, so that the lighting effect reaches the preset brightness when the display panel displays a white picture; the overvoltage driving unit is used for starting a driving function, adjusting the parameter configuration table and performing overvoltage driving on a data line of the display panel based on the parameter configuration table and the target driving voltage so as to improve the charging rate of the heavy-load picture, so that the charging rate is improved by detecting the heavy-load picture and cooperatively adjusting the voltage and overvoltage driving, and the charging efficiency is improved. The method has the advantages of improving the charging rate of a heavy-load picture, eliminating display defects and improving the display quality.

The invention discloses a charging control method and device for a full liquid cooling charging pile and a medium, and the method comprises the steps: collecting the charging information needed by the full liquid cooling charging pile during charging, inputting the charging information into a preset LSTM model, and obtaining a corresponding power grid load prediction value; according to the power grid load prediction value, a charging power upper limit value corresponding to the full liquid cooling charging pile is determined; when it is detected that the full-liquid-cooling charging pile is in the charging state, the battery is charged according to the charging power upper limit value, and a corresponding temperature control protection strategy is executed on a liquid cooling module according to the real-time temperature gradient corresponding to the liquid cooling module in the full-liquid-cooling charging pile; and acquiring a charging rate corresponding to the battery through the battery management system interface, determining that the battery is charged when the charging rate is greater than a preset value, and controlling the full-liquid-cooling charging pile to enter a low-power-consumption mode.

A charging management system includes a network interface, a memory, and a processing circuit including a processor. The processing circuit is configured to determine monetary information related to an energy price, determine an electrical vehicle (EV) power limit PLIM for a total amount of EVs in an EV charging network, transmit the monetary information to two or more agents, each of the two or more agents associated with an EV in the EV charging network, receive, from each of the two or more agents, a bid including: an agent monetary value, a desired charging rate PD, and a charging interval, and allow the EVs associated with the two or more agents to be charged based on each of the bids.