97 results about "Range anxiety" patented technology

The invention relates to the technical field of vehicle batteries, particularly provides a battery SOH estimation method, a control device and a storage medium, and aims to solve the problem that in the prior art, the use scene for detecting the SOH of a vehicle battery is limited. In order to achieve the purpose, the method comprises the steps that S100, in the charging process, an ICA curve of a battery is obtained; and S200, based on the first peak valley position of the ICA curve, obtaining a battery SOH estimation value. According to the method, the complete ICA curve can be complemented and obtained by only measuring a part of the values of the preset charging time, the accurate SOH value is finally obtained, the battery does not need to be fully charged, the application scene of SOH prediction is expanded, and a user is further away from mileage anxiety.

The invention belongs to the technical field of lithium ion battery automobiles, and relates to an online lithium battery automobile remaining mileage prediction method and system, and the method comprises the following steps: collecting vehicle data in a preset process, and selecting variables strongly related to the remaining mileage according to a spearman coefficient rho s among various items of the vehicle data; carrying out data cleaning on the vehicle data corresponding to the strongly correlated variables through a least square regression algorithm, and removing abnormal values; inputting the vehicle data subjected to data cleaning into a two-way stacking gating circulation network for selectively recording and forgetting the vehicle data in the vehicle driving process, and mining a time sequence dependency relationship on line; and inputting the vehicle data and the time sequence dependency relationship into a Kolmogorov-Arnold network to realize nonlinear mapping, extracting intermediate sequence features of the vehicle data, and outputting the remaining mileage of the vehicle. The method can accurately predict the remaining driving mileage, so that a driver can reasonably arrange the journey and plan the charging mode and time, the mileage anxiety is relieved, and the driving experience is improved.

The application provides a highway charging load prediction method and control system based on traffic flow power. Through a second-by-second specific power model of different electric vehicle types on the highway, factors such as road slope, vehicle load, electric vehicle braking recovery characteristics, instantaneous speed and acceleration can be considered to achieve more accurate energy consumption modeling. By establishing a specific power operation mode distribution library of different vehicle types, using a shock wave model and a cellular transmission model to solve, quantifying the congestion propagation process, dynamically correcting the specific power calculation parameters, only the road section parameters and average speed are needed to calculate the energy consumption under complex road conditions. The driver's range anxiety is quantified as a dynamic variable, and charging decision rules are established for different scenarios. The charging probability is dynamically corrected based on the queue length, weather, and driver type, and an electric vehicle charging time prediction model is established based on different service area charging scenarios.

The invention relates to the technical field of hydrogen internal combustion engines, and discloses a hydrogen internal combustion engine power generation system and method based on AI control, and the system comprises the following modules: a receiving module which is used for receiving an operation instruction from a driver, and the operation instruction comprises an expressway power generation instruction and a static charging instruction; the coupling control module comprises a processor unit and an AI control unit; the processor unit is responsible for data transmission operation; the AI control unit is used for receiving the operation instruction, responding to the operation instruction and controlling operation of a vehicle-mounted generator; and the vehicle-mounted generator is connected with the coupling control module and is used for converting hydrogen energy into electric energy. The invention discloses an AI-controlled hydrogen internal combustion engine power generation system and method, and mainly solves the problems of low energy utilization efficiency, poor operation flexibility and incapability of effectively relieving mileage anxiety caused by the fact that a vehicle-mounted range extender of an existing electric vehicle is passively started only by depending on a preset charging state threshold value of a main battery and does not consider the intention of a driver and a stroke situation.

The invention discloses a virtual power plant control method, system and device containing an electric vehicle and a medium, and relates to the field of virtual power plant control, and the method comprises the steps: modeling a virtual power plant control problem as a distributed partial observable Markov decision model; the distributed partial observable Markov decision process comprises a plurality of intelligent agents, the global state of a virtual power plant, joint observation of all the intelligent agents, local observation of all the intelligent agents, joint actions of all the intelligent agents, actions of all the intelligent agents and a reward function; constructing a value network and a strategy network; one agent corresponds to one policy network; performing centralized training on the value network and the strategy networks by using a reinforcement learning method to obtain an optimal control strategy corresponding to the value network and each strategy network; according to the method, user information leakage is prevented, better charging and discharging control performance is realized, the power utilization cost of the electric vehicle is reduced, and the mileage anxiety of the user is reduced.

The invention relates to the field of big data analysis, in particular to an electric vehicle charging station recommendation method and device based on driver charging preference. According to the method, personal information and historical charging behavior data of a current user are collected, and a mileage anxiety threshold L of the user is updated. Collecting state information of a vehicle driven by a current user and operation data of a charging station; when a user puts forward a charging demand, candidate charging stations are screened firstly; calculating the payment cost Cb, the parking time cost Ct, the mileage anxiety cost Ch and the charging utility Ui of the user arriving at any candidate charging station i according to the collected information and the L of the current user; calculating the selection probability Pi of each candidate charging station according to the Ui; and the Ct and the Ch are ranked in a low-to-high order to generate a recommendation list. The problem that the existing charging station recommendation service cannot meet the personalized preference of the user is solved.

The invention provides a personalized endurance mileage recommendation method and system for a storage battery motorcycle user, and relates to the technical field of data processing, and the method comprises the steps: 1, obtaining basic parameters of a storage battery motorcycle, including battery capacity, motor power and average energy consumption data in a standard test environment; 2, on the basis of the basic parameters, actual driving data of the user are collected in real time, and the actual driving data comprise driving road condition types, gradient changes, driving speed fluctuations, starting and stopping frequencies and acceleration or braking behaviors; and real-time coordinates of the battery pack center position, the motor installation position and the vehicle gravity center position of the storage battery motorcycle are detected in real time through a vehicle-mounted sensor. According to the method, the personalized endurance mileage recommendation value is accurately generated and fed back in real time by fusing the vehicle basic parameters, the real-time driving data and the dynamic spatial relationship analysis, so that the mileage anxiety of the user is effectively relieved, and the driving experience and the vehicle energy efficiency optimization capability are improved.

A new energy automobile intelligent charging path planning method suitable for an urban road comprises the following steps: 1) optimizing an original road network to obtain a shortest path diagram among a starting point, each charging station and a terminal point; 2) initializing parameters of the ant colony algorithm and values of pheromones; 3) calculating a heuristic factor between points by considering the position, the power and the end point approaching degree of the charging station; 4) calculating the selected probability weights of the terminal point and each charging station, starting from the starting point by each ant, and selecting a next node according to a pseudo-random proportion rule; 5) calculating the optimal charging time of each path reaching the terminal point, obtaining the total time of reaching the terminal point, and carrying out global and local pheromone updating according to the total time; and 6) repeating the steps 4)-5) until convergence, and using a result with the shortest total time as a final electric vehicle charging path. The problem of mileage anxiety of the electric automobile is solved, a proper charging station is selected for a user, and the travel time is shortened.

A robust range prediction system is presented that uses a range prediction model trained on data relating to the energy usage of an electric vehicle (EV) to estimate the range of the vehicle during operation. The range prediction model may require a greater number of inputs than may be considered by an OEM range estimator provided by the EV. The predicted mileage generated by the mileage prediction system may then be compared to an estimated mileage of the OEM mileage estimator, and / or combined into an integrated display to provide confirmation to a driver of the estimated mileage, which may reduce mileage anxiety of the driver. In addition, the proposed range prediction system may generate recommendations for how to maximize (e.g., maintain or increase) the predicted range by adjusting the operation of the vehicle or coordinating the operation of the vehicle with other vehicles, traffic signals, etc.

The present invention provides a remaining mileage prediction method, system, computer device, and readable storage medium, wherein the remaining mileage prediction method includes: obtaining a future driving route between a current location and a destination location; segmenting the future driving route and obtaining road condition information and temperature change information for the future driving route; calculating a driving habit score based on the driver's operation of the accelerator and brake pedals within a historical unit time; predicting the total energy consumption and unit mileage energy consumption of the future driving route based on the driving habit score, the road condition information, and temperature change information of the future driving route; and calculating and predicting the remaining mileage of the vehicle upon arrival at the destination location based on the total energy consumption and unit mileage energy consumption. Through this application, the estimated remaining mileage is not only calculated with low error and high accuracy, but also avoids the problem of users misjudging future travel plans, which may cause the vehicle to break down halfway, thereby reducing users' mileage anxiety during long-distance travel.

The application discloses an electric vehicle charging pile integrated with wideband impedance measurement, and aims at the problem that the internal state information of a battery cannot be effectively obtained in the charging process of a traditional charging pile. The application discloses an electric vehicle charging pile integrated with wideband impedance measurement, and aims at the problem that the internal state information of a battery cannot be effectively obtained in the charging process of a traditional charging pile. The application discloses an electric vehicle charging pile integrated with wideband impedance measurement, and aims at the problem that the internal state information of a battery cannot be effectively obtained in the charging process of a traditional charging pile. The application discloses an electric vehicle charging pile integrated with wideband impedance measurement, and aims at the problem that the internal state information of a battery cannot be effectively obtained in the charging process of a traditional charging pile. The application discloses an electric vehicle charging pile integrated with wideband impedance measurement, and aims at the problem that the internal state information of a battery cannot be effectively obtained in the charging process of a traditional charging pile. The application discloses an electric vehicle charging pile integrated with wideband impedance measurement, and aims at the problem that the internal state information of a battery cannot be effectively obtained in the charging process of a traditional charging pile. The application discloses an electric vehicle charging pile integrated with wideband impedance measurement, and aims at the problem that the internal state information of a battery cannot be effectively obtained in the charging process of a traditional charging pile. The application discloses an electric vehicle charging pile integrated with wideband impedance measurement, and aims

The utility model relates to a vehicle-mounted solar charging system and a vehicle, and the vehicle-mounted solar charging system is arranged on the roof of the vehicle, and comprises a storage structure which comprises a storage groove and a movable groove door which are arranged on the roof; the solar device comprises a lifting supporting structure, a reel and a flexible solar cell which can be wound on the reel and can be unfolded along the reel. And the lifting support structure is used for driving the reel to lift along the storage groove, so that the flexible solar cell on the reel is stored in the storage groove or extends out of the upper part of the storage groove. According to the scheme, the requirement of a user for auxiliary charging of the vehicle through the solar cell can be met, the mileage anxiety of the user is relieved, the flexible solar cell can be completely stored after charging is finished, the influence of the solar charging system on the appearance and safety of the vehicle is reduced, and the user experience is improved. And the risks of aging, damage and the like of the solar cell caused by long-time exposure of the solar cell outside the vehicle are effectively reduced, and the service life of the solar cell is prolonged.

The invention discloses a new energy pure electric vehicle high-speed battery replacement control method, which is characterized in that an energy complementing road entering from a ramp is arranged outside a main road of a high-speed road, and the energy complementing road is sequentially provided with a power unloading area and a power on area; vehicles driving into the energy complementing road from the high-speed main road sequentially pass through the unloading area and the electrifying area to complete unloading and electrifying processes of the replaceable batteries of the vehicles; when a vehicle runs in an unloading area, the vehicle unlocks a locking mechanism of a battery pack; and in the power-on area, when the battery pack is detected, the battery pack is locked in the battery compartment of the automobile chassis through the battery pack locking mechanism. The method has the advantages that rapid energy supplementation is achieved without stopping in the high-speed driving process, the endurance anxiety is reduced, the endurance of the vehicle is improved, and the purpose of rapidly completing battery replacement is achieved.

The present application relates to the technical field of automobile energy supplement, in particular to a charging energy supplement method and system in automobile travel, the charging energy supplement method in automobile travel comprises obtaining travel information of a vehicle; searching for charging stations in a surrounding area of a route in the travel information, screening the searched charging stations to eliminate stations not meeting predetermined conditions, to obtain candidate charging stations; scoring the candidate charging stations and selecting at least one target charging station; adding the target charging station as a navigation passing point to update the route and guide the vehicle to charge. The present application can solve the problem of charging range anxiety.

The invention belongs to the technical field of vehicle control, and particularly relates to a vehicle energy-saving navigation method and system based on historical behavior learning, and the method comprises the steps: obtaining the travel data of a target vehicle in a historical time period, generating a historical path sequence composed of standard road segment identifiers through map matching, mining a high-frequency passing path of the target vehicle, and obtaining the high-frequency passing path of the target vehicle; according to the speed sequence, track points meeting a preset low-speed condition are identified, and the track points are clustered and verified as intersection waiting points; for each intersection waiting point, establishing a time-dependent waiting probability model according to historical passing records of the intersection waiting point under different time slices; when the target vehicle runs in real time and is matched with a certain high-frequency passing path, inquiring a waiting probability model of a waiting point of a next intersection in front according to the current position, the current time and the vehicle speed; and according to the queried waiting probability value, generating and outputting a hierarchical driving guide instruction to a vehicle end human-computer interaction interface. And a personalized intersection passing memory bank is established for vehicle owners, so that the mileage anxiety is relieved.

This invention relates to the field of big data analytics, and in particular to a method and apparatus for recommending electric vehicle charging stations based on driver charging preferences. The method collects current user information and historical charging behavior data, and updates the user's range anxiety threshold. L The system collects the status information of the user's vehicle and the operational data of the charging stations; when a user submits a charging request, it first filters candidate charging stations; then it combines the collected information with the user's current status. L Calculate the user's arrival at any candidate charging station i Payment costs C b Parking time cost C t Range anxiety costs C h and charging efficiency U i Then according to U i Calculate the selection probability of each candidate charging station P i Finally, based on user preferences, the candidate charging stations were categorized as follows: P i From high to low or by C b , C t and C h The recommendations are generated by sorting the data from lowest to highest quality. This invention addresses the problem that existing charging station recommendation services cannot meet users' personalized preferences.

The invention provides a range extender control method and device, and the method comprises the steps: obtaining a target user intention and vehicle state data, verifying the feasibility of the target user intention based on the vehicle state data, determining a range extender control strategy according to the vehicle state data and the target user intention if the target user intention is feasible, and carrying out the control of a range extender. In this way, a user can be supported to actively participate in control of the range extender, endurance anxiety caused by passive waiting for regulation and control due to the fact that the control logic of the range extender is not clear is avoided, due to the tendency description that the user actively carries out control of the range extender, a certain expectation can be achieved for a possible control strategy, and the user experience is improved. And the discomfort of a user caused by sudden starting or power attenuation of the range extender is reduced.

The utility model discloses a distributed driving system and a vehicle. The distributed driving system comprises an engine, a driving device and a controller, the synchronizing mechanism and the engine can be in a power coupling state or a power disconnection state; the first driving module comprises a first motor and a first speed reducing mechanism, and the power input end of the first speed reducing mechanism is in transmission connection with the first power output end of the synchronizing mechanism and the power output end of the first motor; the second driving module comprises a second motor and a second speed reducing mechanism, and the power input end of the second speed reducing mechanism is in transmission connection with the second power output end of the synchronizing mechanism and the power output end of the second motor; and the coupling and disconnecting mechanism is used for realizing power connection or disconnecting power connection between the first driving module and the second driving module. Compared with the prior art, the engine is integrated in the distributed driving system, so that the endurance mileage is increased, and the mileage anxiety is reduced.

A kind of modular charging battery and battery cell for electric vehicle belong to electric vehicle field.It includes battery body, which is provided with foldable pull structure;Positioning hole structure is arranged above the battery body;Positioning pin structure is arranged below the battery body;The battery body is also provided with power interface and the chip interface of the chip and / or RFID tag with unique identity and charge-discharge times record function.The present application can realize real-time monitoring of battery capacity, charge-discharge times and other functions by cooperating with the identification chip and the matching intelligent electric vehicle, electric vehicle modular battery intelligent charging device and electric vehicle battery modular management system, completely separate battery charging and use scene, quickly complete battery replacement and cost settlement, effectively track the whole life cycle of battery, realize faster and cheaper user experience than refueling, and solve the range anxiety.

The utility model belongs to the technical field of electric two-wheeled vehicle charging, and particularly relates to an electric two-wheeled vehicle charging reminding system which comprises a vehicle control subsystem, a cloud platform and a station control subsystem. The vehicle control subsystem and the station control subsystem are in communication connection with the cloud platform. The vehicle control subsystem is arranged on an electric two-wheeled vehicle, and the station control subsystem is arranged at a charging station; according to the utility model, the vehicle control subsystem monitors the battery electric quantity and the vehicle position in real time, and the station control subsystem monitors the available battery quantity data and available charging pile quantity data of the battery changing cabinet in the battery changing station, and the position data of the battery changing station; the cloud platform obtains the position of a battery replacing station which has an available battery or an available charging pile and is closest to the two-wheeled electric vehicle and feeds back the position to a user, so that the user is reminded of charging in time and the position of the available charging station is provided. According to the utility model, the time and process for searching the charging station by the user can be shortened, and the travel mileage anxiety of the user is reduced.

The application discloses an orderly charging control method for an electric vehicle charging station, comprising the following steps: data acquisition; constructing a double-layer Stackelberg game framework of an upper-layer aggregator and a lower-layer individual user; constructing a user bounded rationality behavior model coupled with a prospect theory, a range anxiety and individual heterogeneity; solving by using a customized SAC algorithm to generate a charging and discharging incentive price and a power instruction; executing feedback and dynamic adjustment; and realizing closed-loop regulation and control of data set updating and model iterative solving through a deviation threshold determination. The application is suitable for power spot market fluctuation environment, has strong algorithm robustness and accurate scheduling, and can improve the operation efficiency of the charging station and the power grid friendliness.

The application provides a charging station intelligent selection method based on road conditions, an electronic device and a storage medium, and the method comprises the following steps: acquiring a current navigation route of a vehicle, wherein the current navigation route is composed of multiple road segments; acquiring road segment energy consumption of each road segment in the multiple road segments; based on current energy of the vehicle and the road segment energy consumption of each road segment, obtaining first node residual power after each road segment is driven to an end; and based on the first node residual power, searching and determining a charging station to be pushed to a user, and the application can improve the prediction accuracy of the charging station to be pushed to the user and reduce the mileage anxiety of the user by dividing the current navigation route into multiple road segments and pushing the charging station to the user based on the residual power after each road segment is driven to an end.

The present invention discloses a method, device, equipment and storage medium for pushing charging and swapping station points. The method includes: when an electric vehicle is powered on, determining a recommended driving condition according to the current vehicle information; when the actual driving condition of the electric vehicle is inconsistent with the recommended driving condition, planning the driving path of the electric vehicle to obtain a charging and swapping planning path; determining a target station according to the station information of each charging and swapping station on the charging and swapping planning path, and displaying the target station. By determining the recommended driving condition based on the vehicle information of the electric vehicle, when the actual driving condition is inconsistent with the recommended driving condition, planning the path of the electric vehicle to obtain a charging and swapping planning path, and displaying the target station determined according to the station information of the charging and swapping station on the charging and swapping planning path, the technical problem of being unable to timely push a suitable charging and swapping station for the user is solved, enabling the user to timely replenish electric energy for the electric vehicle, alleviating range anxiety, and improving the user experience.

The invention discloses a photovoltaic energy storage and charging integrated cooperative control system for an electric vehicle. The system comprises a photovoltaic energy storage cooperative unit, a bidirectional high-voltage connection unit, a vehicle connection unit and a cooperative control unit. The photovoltaic array and the energy storage battery pack are integrated to form a direct-current energy port, and an alternating-current energy bus is constructed through a bidirectional energy conversion device, so that clean energy storage and conversion are realized; the two-way high-voltage connection units are interconnected through an alternating-current bus to realize pluggable two-way electric energy transmission with a vehicle high-voltage loop; the vehicle connection unit is used as a vehicle-mounted special interface to complete vehicle state acquisition and high-voltage safety access; the cooperative control unit integrates a photovoltaic priority scheduling module and an energy recovery control module, executes a clean energy priority supply strategy, dynamically adjusts the energy flow direction, and automatically recovers vehicle feedback energy under the braking working condition. According to the invention, non-impact energy complementation in parking and driving dual scenes is realized, multi-redundancy safety protection is provided, overall modularization is extensible, the utilization rate of clean energy is effectively improved, the problems of endurance anxiety and high-voltage energy complementation safety of the electric vehicle are solved, and the system is suitable for various electric vehicle mobile charging, photovoltaic range extension and emergency energy storage scenes.

The invention discloses a charging pile intelligent regulation and control method considering mileage anxiety and adjustable potential of a user. According to the method, on one hand, the flexibility of the electric quantity demand of each accessed vehicle is considered, an accumulated energy-power boundary model is constructed, and then the adjustable potential of an adjustable electric vehicle in a charging station is calculated; on the other hand, a partially observable Markov model of the charging station is constructed in combination with the mileage anxiety of the user; then, taking each charging pile in the charging station as an agent in a multi-agent reinforcement learning method, and solving a partially observable Markov model of the charging station by using the multi-agent reinforcement learning method; and finally, applying the trained multi-agent reinforcement learning model to the target charging pile, thereby realizing intelligent regulation and control of the charging pile on the charging and discharging power of the accessed vehicle. According to the method, the problems of voltage fluctuation amplitude increase, load peak-valley difference amplification, power distribution network power blockage and the like caused by disordered access of large-scale electric vehicles are solved.

The utility model relates to a rear frame of a hybrid loader, and belongs to the technical field of loader machinery. Comprising a hinge frame, two ends of the hinge frame are fixedly connected with a left side plate and a right side plate respectively, and the left side plate and the right side plate are oppositely arranged; two engine range extender supports and two engine supports are arranged between the left side plate and the right side plate; the two engine range extender supports and the two engine supports are symmetrically fixed to the inner side of the left side plate and the inner side of the right side plate respectively. The rear frame specially provides installation positions of the engine and the engine range extender for the hybrid power type loader, can achieve carrying of hybrid power devices (the engine and the engine range extender) and can relieve mileage anxiety of the hybrid power type loader when the hybrid power type loader is electrically driven.

The application discloses an electric vehicle power battery discharge control method, a computer device and a storage medium. According to the application, the power battery can be discharged according to a dynamically determined discharge cutoff execution value, the state of charge of the power battery can be maintained at a level that just meets the target charging pile, the control of the power battery can be avoided to be too conservative to affect the use of other power components on the electric vehicle, and the control of the power battery can be avoided to be too aggressive to cause over-discharge of the power battery or to cause the power battery to have a low state of charge that cannot support the electric vehicle to drive to the position of the target charging pile. The electric vehicle power battery discharge control method in the embodiment can improve the use flexibility of the electric vehicle and is favorable to reduce or eliminate the range anxiety of a user. The application is widely applied in the technical field of automobiles.

This invention discloses a vehicle intelligent pre-start method based on user driving habits and environmental information. This invention relates to the field of vehicle self-starting technology and solves the problem of starting too early or too late due to insufficient integration with user driving habits, resulting in energy waste or user waiting. This invention determines the maximum energy consumption data through historical route data, calculates available energy consumption by combining it with the vehicle's remaining comprehensive energy consumption, and then verifies and starts the items to be implemented step by step according to the order of the items to be implemented and the energy consumption used, ensuring that the energy consumption during pre-start does not exceed the available energy consumption. This effectively solves problems such as range anxiety for pure electric vehicles and ineffective fuel consumption in gasoline vehicles. Through the design of "prohibiting starting when available energy consumption ≤ 0" and "stopping starting when cumulative energy consumption exceeds the limit," it avoids vehicle starting failures or subsequent energy shortages due to insufficient energy consumption, balancing the comfort of pre-start and the reliability of vehicle operation, and achieving the goal of "starting on demand, energy saving and high efficiency."

A remaining-range display method, comprising: in response to detecting an energy consumption switching signal, obtaining an energy consumption difference between pre-switching energy consumption and post-switching energy consumption; and in response to determining that the energy consumption difference is greater than a preset value, switching a current remaining‐range display interface to a target display interface, so as to display a remaining‐range variation trend via the target display interface. Further provided are a remaining-range display apparatus, an electronic device, and a vehicle. According to the method, the remaining-range variation trend is displayed via the target display interface, so that users can intuitively understand how the current energy consumption switching affects the remaining range, and clearly perceive the dynamic range capability of the whole vehicle, thereby avoiding the problem in the prior art of the range anxiety of users caused by inconsistencies between the displayed remaining-range attenuation and the actual driving range, or instantaneous changes in the displayed remaining range.

The invention discloses a big data analysis method for national and provincial road charging pile layout. Multi-source data such as traffic flow, historical charging requirements and existing charging pile distribution are collected, and a charging facility vacant area is identified in combination with a road network and geographic information. A time sequence prediction method is utilized to predict future charging demands, a multi-target optimization model is established, and a candidate charging pile layout scheme is optimized through linear programming, so that the targets of construction cost minimization, charging demand satisfaction rate maximization, user waiting time minimization and the like are achieved. In combination with MATLAB simulation software, different layout schemes are simulated, the charging pile utilization rate, the service coverage rate and the user experience are evaluated, and decision making is assisted through visual analysis. The method can scientifically plan the arrangement of the charging piles, improves the resource utilization efficiency, relieves the endurance anxiety of the user, and provides a data-driven decision basis for the construction of national and provincial charging infrastructures.