1391results about How to "Improve charging efficiency" patented technology

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.

An energy scheduling system of a high-power liquid cooling charging pile belongs to the technical field of liquid cooling charging piles, and comprises a power scheduling module, a liquid cooling management module, a data acquisition and monitoring module, an energy storage and energy recovery module, a communication and interaction module, an intelligent scheduling module and a remote management and analysis module. Through the intelligent scheduling and energy optimization technology, power distribution can be adjusted in real time according to the vehicle demand and the power grid state, overload is avoided, and the charging efficiency is improved; and secondly, an advanced liquid cooling management technology is adopted, and temperature monitoring and cooling liquid flow rate adjustment are combined, so that heat balance and stable operation of the equipment under a high-load condition are ensured, the service life of the equipment is prolonged, and energy waste is reduced. In addition, the system can store redundant electric energy and release the electric energy in the peak load period of the power grid through the energy storage and energy recovery module, so that the power grid pressure is effectively reduced, and the energy utilization rate is also improved.

The invention discloses a charging pile operation safety management and control system based on artificial intelligence, and belongs to the technical field of charging pile operation safety management and control. A charging pile operation safety management and control system based on artificial intelligence comprises a data acquisition module, a physical environment monitoring module, a central processing unit, a safety evaluation model, a fault detection module, a risk warning and execution module, a multi-charging pile collaborative management module and a user interface. The problems that existing charging pile data collection and environment monitoring are not comprehensive, an intelligent safety evaluation mechanism is lacked, the fault detection and response efficiency is low, and resource allocation is unreasonable are solved. Precise monitoring and safety trend prediction of the operation state of the charging pile are achieved through comprehensive data collection and the safety evaluation model, an intelligent fault detection and grading early warning mechanism can rapidly recognize and respond to potential and existing faults, resource allocation is optimized through the multi-charging-pile collaborative management module, the overall performance is improved, and the system is suitable for large-scale popularization and application. The operation safety is ensured.

The invention provides a remote control method and system for a new energy vehicle charging pile, and the method comprises the steps: collecting a vehicle battery state, a user demand, and the operation information of a power grid and the charging pile, and integrating the information into a standardized comprehensive state variable; dynamically adjusting the initial charging power of the single user according to the health state of the vehicle battery to obtain adjusted charging power; calculating the charging priority of the user by combining the distributed power with a dynamic weight adjustment model based on time decay; receiving a multi-user distribution strategy, and constructing a real-time adjustment variable set in combination with the operation information of the charging pile; and the power grid load change is monitored in real time. According to the invention, on one hand, a flexible solution is provided for personalized demands of users, and on the other hand, efficient utilization and active management of system resources are realized through energy sharing and remote dynamic control, so that main defects in the prior art are overcome, and the system has important technical value and application prospect.

The invention relates to the technical field of lithium battery charging and discharging management, and discloses a lithium battery charging and discharging detection and management method, device and equipment and a storage medium, and the method comprises the steps: carrying out the data collection of the charging and discharging process of a lithium battery pack, applying consistent Gaussian noise, and obtaining an electrode-level expansion data set and a battery-level expansion data set; performing feature mapping and feature mixing by minimizing the maximum average difference loss function to obtain a mapping feature vector; estimating the state of charge and the state of health of the battery through a fusion model of a recurrent neural network and a physical information hybrid neural network to obtain a state of charge estimated value and a state of health estimated value; and constructing a battery pack electric heating model of the lithium battery pack, and generating a corresponding charging and discharging control instruction sequence. Self-adaptive adjustment can be carried out according to the real-time state of the battery, potential safety hazards such as over-charging and over-discharging and out-of-control temperature are effectively avoided, and the use safety of the battery pack is remarkably improved.

The invention provides an electric bicycle charging method and system based on a mutual recognition mechanism, and relates to the technical field of battery management, and the method comprises the steps: detecting the state of a battery through a multi-sensor fusion algorithm, predicting the endurance mileage and charging demands through deep reinforcement learning, and predicting the destination and arrival time through track analysis; a charging pile is optimized based on a multi-constraint path planning model and an improved multi-target genetic algorithm, a target charging pile adopts dual encryption identity authentication, a self-adaptive charging control algorithm based on a fuzzy neural network is used for optimizing a charging process, and data is uploaded to a charging scheduling server.

The invention discloses a new energy charging pile charging control method and system, and relates to the technical field of new energy, and the method comprises the steps: collecting user historical charging data, power grid load data, fixed electricity price information and weather forecast data in real time, and recognizing user charging habits and demands; generating a personalized charging scheduling strategy according to the charging habit of the user and the real-time power grid state; the availability of various energy sources is monitored in real time, the generating capacity and the cost of each energy source are evaluated, the priority of energy source selection is adjusted by using a personalized charging scheduling strategy, and an optimal charging mode is automatically selected; executing charging operation based on the charging mode selected by the user, and performing adjustment according to the power grid load and the energy consumption condition; the availability of various energy sources is monitored in real time, the generating capacity and the cost are evaluated, and the priority of the energy sources is dynamically adjusted, so that the response capability of the charging pile to environment change is improved, the charging cost of a user can be reduced, and renewable energy sources are fully utilized.

The invention belongs to the technical field of path planning, and particularly relates to a charging path planning method for an intelligent mobile charging vehicle, and the method comprises the steps: collecting the three-dimensional data information of a charging scene through a camera and a laser radar, and constructing a three-dimensional space model; image acquisition of a charging scene is carried out through a camera and a laser radar, and a plane navigation map is established; after the mobile charging vehicle receives a charging instruction, performing global path planning based on an improved PSO algorithm to obtain an optimal path; real-time image acquisition is carried out through a camera and a laser radar, local path planning is carried out through an improved DWA algorithm, obstacles are avoided in time, and whether a target point is reached or not is verified; and the charging manipulator grabs the charging wire to perform charging operation. According to the invention, the optimization of global and local path planning is realized, the accuracy and efficiency of path planning are improved, and the charging vehicle can safely and quickly reach the target charging position.

The invention discloses a charging pile output power control method, and particularly relates to the technical field of charging pile management, and the method comprises the following steps: collecting the real-time operation information of a charging station, analyzing the overall load fluctuation condition, and judging whether an early sign that the operation fluctuation intensity is too high exists or not; and if abnormity is identified, further collecting operation information of each charging pile, extracting feature data, and performing stability and adaptability evaluation. And an evaluation result is imported into a fuzzy reasoning model, and the charging pile is divided into a high-quality operation state and a low-quality operation state. In a single abnormal scene, the charging piles in a high-quality operation state maintain a constant-current and constant-voltage strategy, and the charging piles in a low-quality operation state are switched to an adaptive power adjustment strategy; in an overall abnormal scene, all the charging piles are switched to an adaptive power adjustment strategy, so that the operation efficiency and stability are improved; the strategy can be dynamically adjusted according to different operation scenes, and the requirements under different operation conditions are met.

The invention is suitable for the technical field of charging piles, and particularly relates to a charging pile power distribution method and device, equipment and a medium. According to the method, the current charging demand of a target charging pile is collected in real time, when the current charging demand is larger than the charging demand at the last collection moment, the first target number of power modules needing to be added is determined, a first path set of the target charging pile and each remaining available power module is obtained, and according to a preset limiting condition, the first path set is determined; screening the first path set to obtain a screened path set, determining the weight of the corresponding path according to the path parameter of each path in the screened path set, determining a target path according to the first target number and the weight of each path in the screened path set, and controlling the target path to be conducted, according to the invention, the power distribution is dynamically optimized according to the actual charging demand and the power supply condition, so that the charging efficiency can be effectively improved, and the power loss is reduced.

The invention discloses a wireless charging method for an unmanned aerial vehicle group, and the main points of the technical scheme are that the method comprises the following steps: S1, integrating a wireless charging receiving module, a communication module and an electric quantity monitoring module on each unmanned aerial vehicle; s2, when the electric quantity of a certain unmanned aerial vehicle is lower than a preset threshold value, the unmanned aerial vehicle sends a charging request to a nearby unmanned aerial vehicle and / or a charging base station through a communication module; s3, the charging scheduling system selects an optimal charging source (unmanned aerial vehicle or charging base station) and a charging path through an intelligent scheduling algorithm according to the real-time position, the electric quantity and the flight task state of the unmanned aerial vehicle group; s4, the unmanned aerial vehicle receives electric energy from the selected charging source through the wireless electric energy transmission technology, and charging is completed; according to the wireless charging method, efficient charging of the unmanned aerial vehicle group is supported, the optimal charging position is intelligently selected through the automatic moving charging base station, the wireless charging module adapts to different flight attitudes, the collision risk is reduced through the dynamic navigation function, and stable operation in various environments is ensured.

The invention provides a multi-parameter collaborative optimization battery charging and discharging management system integrated with a thermal management technology, and aims to improve the charging and discharging efficiency and safety of a battery and prolong the service life of the battery. The system monitors key parameters such as the temperature, the voltage, the current and the internal resistance of the battery in real time through a high-precision sensor, and the parameters are comprehensively analyzed through the data fusion technology. A core optimization algorithm adopts a genetic algorithm or deep learning, a charging and discharging strategy is dynamically adjusted, and battery performance maximization is achieved. The thermal management module effectively controls the temperature of the battery through a cooling fin, a liquid cooling system or a phase change material, overheating and supercooling are prevented, and the safety and stability of the battery are improved. The user interface is friendly, the battery state is convenient to monitor and adjust, and the system has wide application prospects in the fields of electric automobiles, renewable energy storage and the like.

The invention discloses a wireless charging intelligent regulation and control method and system, and relates to the technical field of wireless charging regulation and control, and the method specifically comprises the following steps: obtaining the charging demand information of each robot in real time, and generating a task priority coefficient and an electric quantity demand index of each robot; and constructing a wireless charging power distribution evaluation model for the generated task priority coefficient and the electric quantity demand index of each robot, generating a priority distribution coefficient of each robot, and evaluating the wireless charging demand level of each robot. Dividing each robot into a high-demand robot, a normal-demand robot and a low-demand robot according to an evaluation result; and according to the division result of each robot, corresponding power distribution strategies are adopted for the robots with different wireless charging demand levels. According to the method, the problems of wireless charging demand difference identification and dynamic allocation of the robot in the intelligent warehousing system are solved, and an efficient and accurate charging resource optimization configuration effect is achieved.

The invention relates to the technical field of charging power management of charging piles, and particularly discloses a charging power distribution method and device for a multi-gun charging pile, and the method comprises the steps: calculating the theoretical power of each charging gun through collecting the battery information, including the current electric quantity, the battery capacity, the rated charging power and the charging demand, of each vehicle in real time; the safety and the stability are comprehensively evaluated according to the dynamic change of the battery temperature and the load rate of the charging gun; according to the method, the charging power can be dynamically adjusted, the safety and the high efficiency of the charging process are ensured, and the problems of battery damage and unstable charging caused by improper power distribution are avoided; the invention further provides a real-time monitoring interface and an alarm mechanism, abnormal conditions can be found and processed in time, and it is ensured that the charging process is carried out smoothly.

The invention discloses a charging station loss prediction method based on an LSTM deep learning method, and relates to the technical field of charging stations, and the method comprises the following steps: 1, collecting data including real-time power load data, a power grid topological structure and time sequence data; 2, feature engineering: carrying out preprocessing and feature extraction on the data, and extracting expert knowledge features; step 3, establishing an LSTM model in combination with a PPO algorithm; 4, performing hyper-parameter tuning on the LSTM model through a random search method; and step 5, the optimized miniaturized model is then deployed to each charging station, and local real-time energy loss prediction is realized. In order to further improve the prediction accuracy, expert knowledge is creatively integrated in a feature engineering part, multi-dimensional loss feature recognition is carried out, and the performance of the model in processing a complex nonlinear relation is improved by combining the input of an electric power system expert, recognizing factors such as equipment aging and the like.

The invention relates to the technical field of charging management, and discloses an intelligent charging management method, device and equipment for an electric scooter and a storage medium, and the method comprises the steps: carrying out the parameter collection and initialization setting of a single-phase bidirectional converter and a permanent magnet synchronous motor in the electric scooter, obtaining system basic parameters and communication data, and obtaining a network authentication identifier and a charging station operation parameter. And dynamic planning of a charging strategy is executed according to the parameters to generate a segmented charging control curve. And the data are input into the self-adaptive prediction controller to realize real-time adjustment in the charging process, and charging state data and power compensation parameters are obtained. And adopting a double-neural network model structure to obtain a battery safety feature matrix and a fault probability vector. And constructing a three-dimensional charging state space model to carry out optimization calculation on the power compensation parameters, inputting a deep reinforcement learning network to carry out iterative optimization, and generating charging control parameters of the next period, thereby improving the charging efficiency and the electric energy quality of the electric scooter.

The invention discloses a dynamic power distribution method for a new energy charging module, and relates to the technical field of electric vehicle power distribution, and the method comprises the following steps: S1, determining the charging power distribution of the corresponding priority of an electric vehicle; s2, the charging power distribution of the electric vehicle and the state of the electric vehicle are adjusted in real time; s3, classifying the charged electric vehicles; and S4, dynamically adjusting the power distribution of the charging module. By dividing the charged electric vehicles into controllable electric vehicles and uncontrollable electric vehicles, selective power supply can be carried out on the charging module of the charging pile according to the types of the electric vehicles, for the controllable electric vehicles, the utilization rate of the charging station can be increased while the charging module does not exceed the rated power, and for the uncontrollable electric vehicles, the utilization rate of the charging station can be increased while the charging module does not exceed the rated power. The power output of the charging modules is dynamically adjusted through the alternate distribution strategy, the loss degree of each charging module is reduced, and the stability of the equipment is improved while the user requirements can be greatly met.

The invention discloses a different-floor distribution method for a solar auxiliary charging unmanned aerial vehicle in a shielding scene, and the method comprises the steps: obtaining a user set # imgabs0 # for the unmanned aerial vehicle to carry out the distribution service for different floors, obtaining the height of each user as # imgabs1 #, obtaining the required distribution time as # imgabs3 # for a user # imgabs2 #, enabling # imgabs4 # to be the earliest delivery time of a user # imgabs5 #, and enabling # imgabs2 # to be the earliest delivery time of the user # imgabs2 # to be the earliest delivery time of the user # imgabs2 #; the # imgabs6 # is the latest goods receiving time of the # imgabs7 # of the user; the unmanned aerial vehicle selects a user with the earliest delivery time as a target delivery user, and updates a user set which can be delivered by the # imgabs8 # unmanned aerial vehicle at the moment; and carrying out multi-round delivery or hovering charging according to the height # imgabs9 of the floor where the user is located, the shadow height of the obstacle at the target delivery building and the earliest delivery time of the # imgabs10 of the user. The method is an unmanned aerial vehicle multi-round distribution method, and the unmanned aerial vehicle can be charged by searching a proper sunshine irradiation area in a scene with shelters, so that the flight time is prolonged.

The invention discloses a lithium battery charging and discharging control method and system, a product and a medium, and relates to the field of charging control, and the method comprises the steps: collecting the terminal voltage and charging and discharging current data of a current battery, and calculating the state of charge and the state of health of the current battery according to the terminal voltage and the charging and discharging current data; collecting surface temperature data of the current battery, and judging whether the surface temperature data is within a preset safety interval range or not; if yes, a preset charging curve corresponding to the charge state, the health state and the surface temperature data is called from a preset battery model database, and the preset charging curve comprises a plurality of charging stages; based on the charge state, the health state and the surface temperature data, carrying out segmented correction on the charging multiplying power and cut-off voltage of the preset charging curve to obtain an optimal charging curve; and charging the current voltage based on the optimal charging curve. By implementing the method, the charging efficiency of the lithium battery can be improved.

The invention discloses a charging pile intelligent control method and system based on face recognition, and relates to the technical field of information security, and the method comprises the steps: collecting a user face image through a camera when a user gets close to a charging pile, and extracting a user face feature vector through a lightweight algorithm; matching the user face feature vector with a user face feature vector pre-stored in a local database, and verifying user identity information; based on the user identity information passing verification, the charging authority bound with the user identity information is distributed, meanwhile, the relation between the user and the vehicle is verified, and a charging scheme is dynamically generated in combination with user historical charging preference information and charging initial data; charging is started according to the charging scheme, and charging parameters are dynamically adjusted by monitoring real-time charging data in the charging process in real time; the face recognition technology, personalized charging scheme generation and real-time charging parameter dynamic adjustment are introduced, and the intelligent level and user experience of the charging pile system are remarkably improved.

The invention relates to the technical field of batteries, in particular to an intelligent battery discharging control method and system and charging and discharging equipment, and the method comprises the steps that port insertion equipment carries out protocol identification, and the residual maximum power of current theoretical output is calculated according to the maximum output power; when the residual available power cannot meet the port power under the condition that the minimum output power of each port is reserved, other ports are distributed according to the reserved minimum power, and the sum of the minimum power of other ports is subtracted from the residual available power to obtain the actual output power of the port; and monitoring the actual discharge power of each port in real time, and limiting the maximum discharge power of other ports according to the actual discharge power. According to the intelligent power distribution method, the power output can be dynamically adjusted according to the power demand of the connected equipment, and each piece of equipment can be charged at the fastest speed to improve the charging efficiency.

The invention belongs to the technical field of battery maintenance, and discloses a new energy automobile battery maintenance device which comprises a base, mounting grooves are formed in the upper surface of the base at equal intervals, clamping grooves are symmetrically formed in the front side and the rear side of the bottom of each mounting groove, a mounting shell is fixedly mounted on the upper surface of the base, and a plurality of guide grooves are formed in the upper surface of the mounting shell at equal intervals. Side grooves are symmetrically formed in the side faces of the guide groove, and electric heating plates fixedly sleeve the middles of the front side groove and the rear side groove. Mercury in the telescopic sleeve is heated to expand, so that the expanded mercury in the telescopic sleeve pushes the telescopic end of the telescopic sleeve to move upwards, the telescopic end of the telescopic sleeve drives the heat conducting plate to move upwards through the electric plate to be in contact with the heat dissipation plate, and at the moment, the heat dissipation plate dissipates heat of the battery through the sleeve column and the heat conducting plate; therefore, the problems that the charging and discharging efficiency of the battery is low and the service life is shortened when the battery works in a high-temperature or low-temperature environment are solved.

The invention discloses an energy storage cabinet temperature control method based on a cloud platform and a temperature control energy storage cabinet, and relates to the technical field of electric energy storage, the energy storage cabinet comprises a cabinet body, an energy storage module, a data acquisition module, a communication module and a temperature control module, and the temperature control method comprises the following steps: S1, acquiring environmental parameters and battery state data; s2, determining a temperature adjustment factor of the energy storage cabinet through the battery state data; s3, generating a composite temperature index based on the environmental parameters and the temperature adjustment factor; s4, performing region division on the energy storage cabinet, determining temperature requirements of different regions according to the composite temperature index, and formulating an energy storage cabinet temperature control strategy based on the temperature requirements in combination with the environment prediction temperature; s5, the cloud platform generates a control instruction based on the temperature control strategy and issues the control instruction to the energy storage cabinet to execute the control instruction; accurate control over the temperature in the energy storage cabinet can be achieved, it is ensured that energy storage equipment operates within the optimal temperature range, the energy storage efficiency is improved, and the service life of the equipment is prolonged.

The invention discloses an overcharge control method and system for an electric vehicle, and relates to the technical field of overcharge control, and the method can accurately predict and evaluate the temperature change of a battery by collecting battery data in real time in the overcharge process and combining a normalized data set and a charging feature vector set. Particularly, by constructing a heat and temperature algorithm model, the system can predict the change trend of the battery temperature in the overcharge process. And when the predicted temperature value Tb exceeds the temperature threshold T, the system can immediately trigger an adaptive charging power and cooling system cooperation mechanism, and automatically adjust the overcharge power Pya and the cooling power Pcool. Through the mechanism, when the battery temperature is close to the safety upper limit, the overheating risk can be effectively avoided, and the safety of the charging process is ensured. According to the measure, the accuracy of battery temperature management is remarkably improved, the risk of battery damage caused by abnormal temperature is reduced, and the service life of the battery is prolonged.

The invention relates to the technical field of electric vehicle charging, in particular to a self-adaptive current regulation electric vehicle charging method, which comprises the steps of monitoring battery parameters of an electric vehicle in real time, analyzing the health state of a battery based on the monitored battery parameter data, and predicting the optimal charging current demand of the battery by utilizing a machine learning algorithm. Generating a charging current curve adaptive to the current battery state, dynamically adjusting the charging current according to the predicted charging current curve, starting a cooling or heating system according to the temperature change condition in the charging process, continuously monitoring the voltage, temperature and current change conditions of the battery in the charging process, and starting the cooling or heating system when the battery reaches a preset charging upper limit. And the charging current is gradually reduced, and a charging report is generated after charging is completed. The charging efficiency is improved, the service life of the battery is prolonged, the safety of the charging process is enhanced, detailed charging information is provided for a user, and monitoring and maintenance of the battery are facilitated.

The utility model discloses a multi-protocol compatible fast charging control device which is provided with a first interface unit, a second interface unit, a main control unit and a power supply control unit, the first interface unit is used for connecting power supply input equipment, and the second interface unit is used for connecting equipment to be charged. The main control unit obtains a fast charging protocol supported by the power input device or the to-be-charged device, and controls the power control unit to charge the to-be-charged device according to the fast charging protocol. The main control unit establishes fast communication and matches a corresponding fast charging protocol according to the power supply input device and the to-be-charged device which are connected to the first interface unit and the second interface unit respectively, and then the power supply control unit provides fast charging for the to-be-charged device through the power supply input device, so that adaptive matching of the power supply input device and the to-be-charged device can be realized; according to the fast charging control device, mutual conversion among multiple charging protocols can be realized without manual matching, the compatibility of the fast charging control device is improved, the circuit structure is simple, and the charging efficiency is also improved.

The invention relates to an electric vehicle charging interface identification and positioning system for a charging robot. The system comprises a data acquisition module, a preprocessing module, a charging interface identification module, a positioning module, a posture estimation module, a control module, an environment adaptation module and an automatic learning module. According to the system, images and three-dimensional point cloud data of a vehicle are collected through a camera and a laser radar, the two-dimensional position of a charging interface is automatically recognized through preprocessing and a deep learning model, and the spatial position and posture of the interface are accurately positioned by combining a least square method with three-dimensional coordinates. The control module drives the mechanical arm to be in butt joint with the plug through PID feedback control and A * path planning, and automatic charging is achieved. And the environment adaptation module combines data enhancement and adaptive correction to improve the recognition stability of the system in complex environments such as illumination and background change. The method improves the recognition precision and real-time performance of the charging robot in different environments, and is suitable for an unattended automatic charging scene.

The invention relates to the technical field of lithium battery protection boards, in particular to an intelligent charging and discharging management system based on a lithium battery protection board, and solves the problems that in the prior art, although important guarantee is provided for safe use of a lithium battery, some defects still exist, the protection board fails, and the lithium battery protection board is prone to damage in the long-term use process. And potential safety hazards such as over-charging, over-discharging, short circuit and the like of the battery cannot be effectively prevented. An intelligent charging and discharging management system based on a lithium battery protection board comprises system initialization, real-time battery state monitoring, charging management, discharging management, battery cell balance management, fault diagnosis and early warning, data recording and analysis, and system dormancy and awakening. According to the intelligent charging and discharging management system based on the lithium battery protection board, the service efficiency of the battery is improved, the service life of the battery is prolonged, through accurate electric quantity monitoring and intelligent charging and discharging management, the system can avoid the phenomena of over-charging, over-discharging and over-current of the battery, and therefore the service life of the battery is effectively prolonged.

The invention discloses a charging control method and system of a super charging pile, and relates to the field of super charging, and the method comprises the steps that the super charging pile responds to a charging signal of a vehicle, and sends an initial handshake signal to the vehicle; the super charging pile responds to a received response signal returned by the vehicle, handshake with the vehicle is established according to the response signal, and a charging protocol and a communication protocol of the vehicle are determined according to the response signal; the super charging pile obtains vehicle information of the vehicle according to the communication protocol and sends the vehicle information to the service terminal, the response signal is generated by the vehicle based on the initial handshake signal, and the vehicle information comprises battery information and charging parameters; and the super charging pile responds to the received charging strategy sent by the service terminal, and the charging strategy is executed according to the charging protocol to charge the vehicle. According to the invention, the vehicle can be effectively charged, so that the service life of a vehicle battery is effectively prolonged.

The invention provides a multi-pile charging control method and device, a vehicle, a medium and a program product, and relates to a battery management system technology. The method comprises the steps that under the condition that parameter configuration of a plurality of charging piles is completed, request current is sent to each charging pile in the plurality of charging piles according to battery pack demand current of a vehicle and the number of the charging piles; the actual output capacity of each charging pile is obtained; and dynamically adjusting the request current of each charging pile according to the actual output capability of each charging pile.