A direct alternating multi-modal adaptive allocation method and system for charging piles

Abstract

The application discloses a direct-current alternating-current multi-modal adaptive allocation method and system for a charging pile. First, the charging area information and meteorological prediction data of the location of the charging pile are obtained. When a vehicle is connected to the charging pile, the parking start time and vehicle type information are recorded. Through a pre-trained parking duration estimation model, the corresponding estimated parking duration is generated in combination with the charging area information, meteorological prediction data, parking start time and vehicle type information. At the same time, the ambient temperature, humidity and wind speed data of the location of the charging pile, as well as the charging specification information, current battery capacity and battery temperature data of the parked vehicle are collected. Based on the estimated parking duration and the above real-time environmental parameters and vehicle battery state data, the optimal direct-current charging duration and alternating-current charging duration allocation scheme is determined. Finally, according to the allocation scheme, the vehicle is charged in direct-current charging mode and alternating-current charging mode respectively, realizing the adaptive allocation of direct-current and alternating-current charging modes of the charging pile.

Description

Technical Field

[0001] This application relates to the field of charging piles, and in particular to a DC / AC multimodal adaptive allocation method and system for charging piles. Background Technology

[0002] With the rapid development of the new energy vehicle industry, charging piles, as the core infrastructure supporting the popularization of electric vehicles, are increasingly highlighting their technical characteristics and application limitations. Currently, the mainstream charging technologies in the market are divided into two forms: AC charging piles and DC charging piles, each with different technical principles and application scenarios.

[0003] AC charging stations have a relatively simple structure and low cost, making them suitable for slow charging in scenarios such as homes and offices. However, AC charging stations have significant drawbacks. First, charging time is too long, requiring 6 to 10 hours for a single charge, which fails to meet users' needs for rapid charging, especially during long-distance travel or emergency use, where the long waiting time severely impacts the user experience. Second, because they rely on onboard chargers for energy conversion, charging efficiency is relatively low, and the power of onboard chargers limits the potential for increasing charging speed. Furthermore, in large-scale applications, the low power characteristics of AC charging stations necessitate a greater number of charging points to meet service demand, increasing land use costs and operational complexity.

[0004] DC charging stations offer fast charging speeds, effectively alleviating range anxiety and making them suitable for locations requiring quick turnaround, such as highway service areas and commercial districts. However, DC charging stations also have significant technical drawbacks. High-power charging places a substantial strain on the power grid, requiring dedicated power distribution infrastructure and increasing grid upgrade and maintenance costs. More importantly, high-power fast charging negatively impacts battery life; frequent high-current charging accelerates battery capacity degradation, affecting the lifespan and residual value of electric vehicles. Summary of the Invention

[0005] This application provides a DC / AC multimodal adaptive allocation method for charging piles, including the following steps:

[0006] A1, obtain the charging area information and weather forecast data of the preset location of AC / DC charging piles;

[0007] A2, when a pre-defined parked vehicle connects to the AC / DC charging pile, obtain the corresponding parking start time and vehicle type information;

[0008] A3 generates the corresponding estimated parking duration based on charging area information, weather forecast data, parking start time and vehicle type information through a pre-trained parking duration estimation model.

[0009] A4, obtain the ambient temperature data, ambient humidity data and ambient wind speed data of the location of the AC / DC charging pile;

[0010] A5, obtains charging specification information, current battery power data, and current battery temperature data of parked vehicles;

[0011] A6 determines the corresponding DC charging time and AC charging time based on the estimated parking time, ambient temperature data, ambient humidity data, ambient wind speed data, charging specification information, current battery power data, and current battery temperature data.

[0012] A7, the parked vehicle is charged according to the DC charging time and AC charging time using preset DC charging mode and preset AC charging mode respectively.

[0013] By adopting the above technical solution, the DC / AC multimodal adaptive allocation method of the charging pile can integrate multi-dimensional data such as charging area information, meteorological data, and vehicle information, use a pre-trained model to estimate the corresponding estimated parking time, and combine real-time environmental parameters and vehicle battery status to intelligently allocate DC and AC charging time, so as to maximize charging efficiency and optimize battery protection.

[0014] Optionally, the DC / AC multimodal adaptive tuning method for the charging pile further includes the following steps for obtaining vehicle type information:

[0015] B1, acquire vehicle image data of the parked vehicle;

[0016] B2, determine the corresponding vehicle color information based on vehicle image data;

[0017] B3, attempting to obtain the VIN code data of the parked vehicle;

[0018] B4. If the VIN code data is successfully obtained, the corresponding vehicle type information is determined according to the VIN code data through the preset VIN code lookup table, and the vehicle color information is added to the vehicle type information.

[0019] B5. If the VIN code data acquisition fails, the corresponding vehicle type identification information is generated based on the vehicle image data of the parked vehicle using a preset vehicle identification algorithm.

[0020] B6 generates vehicle type information by combining vehicle color information and vehicle type identification information.

[0021] By adopting the above technical solution, the DC / AC multimodal adaptive allocation method for the charging pile employs a dual identification mechanism. It prioritizes obtaining accurate vehicle type information by querying the VIN code database. When VIN code acquisition fails, it automatically switches to a backup scheme based on vehicle image recognition, ensuring the reliability and fault tolerance of vehicle identification. At the same time, vehicle color information is integrated into the vehicle type information as an important supplementary identifier, enriching the vehicle type information and providing a more comprehensive data foundation for subsequent charging strategy formulation.

[0022] Optionally, step A3 includes the following steps:

[0023] A301 determines the corresponding area type code value based on the charging area information and a preset area type lookup table;

[0024] A302, determine the corresponding meteorological time series data based on meteorological forecast data and preset meteorological time series;

[0025] A303 generates corresponding vehicle type word vector data based on vehicle type information using a preset word vector algorithm;

[0026] A304 generates comprehensive vehicle environment data by combining regional type code values, meteorological time series data, parking start time and vehicle type word vector data.

[0027] A305 generates corresponding vehicle environment feature data based on comprehensive vehicle environment data using a preset feature extraction algorithm.

[0028] A306, based on the vehicle environmental characteristic data, generates the corresponding estimated parking duration through the parking duration prediction model.

[0029] By adopting the above technical solution, the DC / AC multimodal adaptive allocation method for charging piles can standardize and vectorize multidimensional heterogeneous data such as regional type, meteorological conditions, parking time, and vehicle type through systematic data preprocessing and feature engineering, thereby constructing a comprehensive vehicle environment data model. Furthermore, by mining the inherent correlation between data through feature extraction algorithms, it provides high-quality input features for machine learning models, which can improve the accuracy and stability of parking time prediction and provide reliable data support for subsequent charging time allocation.

[0030] Optionally, step A6 includes the following steps:

[0031] A601 calculates the corresponding effective charging time by multiplying the estimated parking time and the preset effective charging time coefficient.

[0032] A602, determine the maximum DC charging power accepted by the vehicle based on the charging specification information, obtain the maximum DC output power of the AC charging pile, and determine the minimum value between the maximum DC charging power accepted by the vehicle and the maximum DC output power of the charging pile and define it as the DC charging base power.

[0033] A603 calculates the corresponding environmental correction factor based on ambient temperature data, ambient humidity data, and ambient wind speed data using a preset environmental correction factor algorithm.

[0034] A604 calculates the corresponding target threshold DC charging amount based on the current battery power data and the preset target power threshold.

[0035] A605, calculates the corresponding target charge DC charging time based on the target threshold DC charging amount and DC charging base power;

[0036] A606, the corresponding DC charging ratio coefficient is calculated and determined based on the environmental correction factor, the current battery temperature data and the preset DC charging time base ratio coefficient.

[0037] A607, calculate the corresponding maximum DC charging time by multiplying the effective charging time and the DC charging ratio coefficient;

[0038] A608, the minimum value between the target DC charging time and the maximum DC charging time is defined as the DC charging time;

[0039] A609 determines the AC charging time by calculating the difference between the effective charging time and the DC charging time.

[0040] By adopting the above technical solution, the DC / AC multimodal adaptive allocation method of the charging pile can achieve a dynamic balance between charging efficiency and battery protection by comprehensively considering multiple constraints such as vehicle charging capacity, charging pile output limitations, environmental factor correction, and battery safety protection. By using a dual constraint mechanism (target power demand and environmental safety constraints) to determine the optimal DC charging time, the remaining time is automatically allocated for AC charging. This ensures that the demand for fast charging is met while avoiding damage to the battery caused by excessive DC charging. It realizes the intelligence, safety, and personalization of the charging strategy, and significantly improves the overall performance of the charging system and the user experience.

[0041] Optionally, step A7 includes the following steps:

[0042] A701, defines DC charging duration as the remaining DC charging duration;

[0043] A702, charge the parked vehicle in DC charging mode according to the remaining DC charging time, and record the DC charging execution time;

[0044] In DC charging mode, the A703 obtains battery charging temperature window data according to a preset temperature monitoring window.

[0045] A704 determines the current charging battery temperature and battery temperature trend slope based on battery charging temperature time window data.

[0046] A705, If the current charging battery temperature is greater than or equal to the preset DC charging battery temperature warning threshold, and the battery temperature trend slope is greater than or equal to the preset temperature slope warning threshold, then proceed to step A707.

[0047] A706, If the current charging battery temperature is greater than or equal to the preset DC charging battery temperature danger threshold, then proceed to step A707.

[0048] A707 updates the remaining DC charging time by decrementing it based on the DC charging execution time, and switches to AC charging mode to charge the parked vehicle.

[0049] A708, in AC charging mode, obtains battery charging temperature window data based on temperature monitoring window and determines the corresponding current charging battery temperature and battery temperature trend slope.

[0050] A709, If the current charging battery temperature is less than or equal to the preset DC charging battery temperature switching threshold, and the battery temperature trend slope is less than or equal to the preset temperature slope switching threshold, and the remaining DC charging time is greater than zero, then execute step A702.

[0051] A710: If the remaining DC charging time is zero, switch to AC charging mode to charge the parked vehicle until the current battery power data is greater than or equal to the preset maximum power threshold.

[0052] By adopting the above technical solution, the DC / AC multimodal adaptive matching method of the charging pile can achieve seamless adaptive switching between DC and AC charging modes by continuously monitoring the battery temperature change trend and battery temperature value, setting multiple safety thresholds and judgment logic. It can not only protect the battery safety in time when the battery temperature is abnormal, but also automatically restore efficient DC charging after the temperature returns to normal. It maximizes the advantages of DC fast charging while ensuring the safety of the charging process, and achieves a balance between charging efficiency and battery life protection.

[0053] Optionally, the DC / AC multimodal adaptive allocation method for the charging pile further includes the following steps:

[0054] B1, when charging the parked vehicle in DC charging mode, record the corresponding DC time period data;

[0055] B2, determine the actual DC charging duration based on DC period data statistics;

[0056] B3, when charging the parked vehicle in AC charging mode, record the corresponding AC time period data;

[0057] B4. Determine the actual AC charging time based on AC time period data statistics;

[0058] B5 calculates the corresponding vehicle charging cost based on the actual DC charging duration, the preset DC charging unit price, the actual AC charging duration, and the preset AC charging unit price.

[0059] By adopting the above technical solution, the DC / AC multimodal adaptive allocation method for charging piles can accurately calculate costs by recording and statistically analyzing the actual execution time of DC and AC charging modes in real time and combining them with their respective billing prices. This achieves the effective implementation of differentiated pricing strategies, ensuring not only the accuracy and transparency of billing but also reflecting the reasonable pricing of different cost structures for DC fast charging and AC slow charging. It provides users with clear cost details, while also providing charging operators with flexible business model support and improving the commercial operation efficiency of charging services.

[0060] Optionally, the DC / AC multimodal adaptive allocation method for the charging pile further includes the following steps:

[0061] C1, based on a preset statistical period, obtains the actual parking time and estimated parking time of each parked vehicle from a preset historical vehicle charging database;

[0062] C2, calculate the corresponding effective parking time ratio by quoting the actual parking time and the estimated parking time of the parked vehicle;

[0063] C3, if the effective parking time ratio of the parked vehicle is greater than 1, then the effective parking time ratio is assigned to 1.

[0064] C4, based on the proportion of effective parking time of all parked vehicles within the statistical period, determines the corresponding typical parking time proportion and defines it as the effective charging time coefficient.

[0065] By adopting the above technical solution, the DC / AC multimodal adaptive allocation method of the charging pile can automatically adjust the effective charging time coefficient by continuously collecting and analyzing the deviation between the actual parking time and the estimated parking time, thereby realizing intelligent iterative optimization of system parameters. This not only continuously improves the estimation accuracy based on actual operating data, but also ensures the stability and accuracy of charging allocation in long-term operation.

[0066] This application also provides a DC / AC multimodal adaptive dispatching system for charging piles, including:

[0067] Image acquisition module;

[0068] Environmental monitoring module;

[0069] AC / DC charging module;

[0070] Processing control module;

[0071] The image acquisition module, the environment detection module, and the DC / AC charging module are respectively connected to the processing and control module.

[0072] The environmental detection module includes a temperature detection module, a humidity detection module, and a wind speed detection module, and the temperature detection module, the humidity detection module, and the wind speed detection module are respectively connected to the processing and control module.

[0073] The DC / AC charging module includes a DC charging module, an AC charging module, a vehicle connection module, and a communication module. The DC charging module, the AC charging module, and the communication module are electrically connected to the vehicle connection module, and the communication module is communicatively connected to the processing and control module.

[0074] The DC / AC multimodal adaptive allocation system of the charging pile further includes an adaptive charging strategy, comprising the following steps:

[0075] D1, obtain the charging area information and weather forecast data of the location of the AC / DC charging module;

[0076] D2, when a pre-defined parked vehicle connects to the AC / DC charging module, obtains the corresponding parking start time and vehicle type information;

[0077] D3, the processing and control module generates the corresponding estimated parking time based on the charging area information, meteorological forecast data, parking start time and vehicle type information through a pre-trained parking time estimation model;

[0078] D4, the environmental detection module acquires the ambient temperature data, ambient humidity data and ambient wind speed data of the location of the AC / DC charging pile;

[0079] D5, obtains the charging specification information, current battery power data and current battery temperature data of the parked vehicle through the AC / DC charging module;

[0080] D6, the processing and control module determines the corresponding DC charging time and AC charging time based on the estimated parking time, ambient temperature data, ambient humidity data, ambient wind speed data, charging specification information, current battery power data and current battery temperature data;

[0081] D7, the DC / AC charging module charges the parked vehicle using preset DC charging mode and preset AC charging mode according to the DC charging time and AC charging time, respectively.

[0082] By adopting the above technical solution, the DC / AC multimodal adaptive allocation system of the charging pile can integrate multi-dimensional data such as charging area information, meteorological data, and vehicle information, use a pre-trained model to estimate the corresponding estimated parking time, and combine real-time environmental parameters and vehicle battery status to intelligently allocate DC and AC charging time, so as to maximize charging efficiency and optimize battery protection.

[0083] In summary, this application includes at least one of the following beneficial technical effects:

[0084] 1. Through systematic data preprocessing and feature engineering, multi-dimensional heterogeneous data such as regional type, weather conditions, parking time and vehicle type can be standardized, encoded and vectorized to construct a comprehensive vehicle environment data model. By extracting features, the inherent correlation between data can be mined, providing high-quality input features for machine learning models. This can improve the accuracy and stability of parking time prediction and provide reliable data support for subsequent charging time allocation.

[0085] 2. By comprehensively considering multiple constraints such as vehicle charging capacity, charging pile output limitations, environmental factor correction, and battery safety protection, a dynamic balance between charging efficiency and battery protection is achieved. By adopting a dual constraint mechanism (target power demand and environmental safety constraints) to determine the optimal DC charging time, the remaining time is automatically allocated for AC charging. This ensures that the demand for fast charging is met while avoiding damage to the battery caused by excessive DC charging. This achieves intelligent, safe, and personalized charging strategies, significantly improving the overall performance of the charging system and the user experience.

[0086] 3. The DC / AC multimodal adaptive matching method of the charging pile can achieve seamless adaptive switching between DC and AC charging modes by continuously monitoring the battery temperature change trend and battery temperature value, setting multiple safety thresholds and judgment logic. It can not only protect the battery safety in time when the battery temperature is abnormal, but also automatically resume efficient DC charging after the temperature returns to normal. It maximizes the advantages of DC fast charging while ensuring the safety of the charging process, and achieves a balance between charging efficiency and battery life protection. Attached Figure Description

[0087] Figure 1 This is a schematic diagram of the process of a DC / AC multimodal adaptive allocation method for charging piles according to the present invention.

[0088] Figure 2This is a schematic diagram of the principle of a DC / AC multimodal adaptive allocation system for a charging pile according to the present invention. Detailed Implementation

[0089] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0090] The embodiments of this application will now be described in further detail with reference to the accompanying drawings.

[0091] refer to Figure 1 This invention provides a DC / AC multimodal adaptive allocation method for charging piles, used to dynamically switch and adjust the charging mode of DC / AC charging piles between DC charging mode and AC charging mode, including the following steps:

[0092] A1, obtain the charging area information and weather forecast data of the preset location of AC / DC charging piles;

[0093] DC / AC charging piles are pre-installed charging piles that have both DC and AC charging capabilities. They can switch between DC and AC charging modes as needed to charge electric vehicles.

[0094] The charging area information is the location information of the AC charging pile, such as shopping mall area, residential area or office area. Vehicles parked in different areas generally have different parking patterns. The parking time of the vehicle can be estimated based on the charging area information, and then different charging plans can be set.

[0095] Meteorological forecast data is the forecast data of the weather for a period of time in the future, such as temperature, humidity, wind speed, rainfall, cloud cover, etc. Meteorological forecast data can predict the impact of weather on battery temperature and heat dissipation during vehicle charging to a certain extent.

[0096] Meanwhile, weather forecasts also affect the parking time of vehicles to some extent. For example, heavy rainfall can extend the parking time.

[0097] A2, when a pre-defined parked vehicle connects to the AC / DC charging pile, obtain the corresponding parking start time and vehicle type information;

[0098] The parked vehicles are those that need to be charged.

[0099] The parking start time is the moment when the parked vehicle connects to the AC / DC charging pile;

[0100] Vehicle type information refers to the vehicle type information corresponding to the parked vehicle. It can include various information such as brand, model, vehicle type, and color. It can generally be obtained by communicating with the parked vehicle through the charging interface, such as by obtaining vehicle type information through the VIN code.

[0101] Vehicle type information can be used to predict the intended use of a vehicle or the habits of its owners. For example, for commercial vehicles, a uniform brand, model and color are usually selected, and commercial vehicles do not stay for long periods of time, so DC charging mode can be used to improve charging efficiency. For private vehicles, different ratios of DC charging and AC charging can be set according to the parking habits of people at the station.

[0102] A3 generates the corresponding estimated parking duration based on charging area information, weather forecast data, parking start time and vehicle type information through a pre-trained parking duration estimation model.

[0103] The parking duration prediction model is a model that is pre-trained based on historical or simulated data.

[0104] The estimated parking duration is the length of time a vehicle may stay, generated by a parking duration prediction model based on multi-angle data.

[0105] A4, obtain the ambient temperature data, ambient humidity data and ambient wind speed data of the location of the AC / DC charging pile;

[0106] The ambient temperature data refers to the temperature data of the surrounding environment where the AC charging pile is located, that is, the temperature data around the parked vehicle.

[0107] The ambient humidity data refers to the humidity data of the surrounding environment where the AC charging pile is located, that is, the humidity data around the parked vehicle.

[0108] The ambient wind speed data refers to the wind speed data of the surrounding environment where the AC charging pile is located, that is, the wind speed data around the parked vehicle.

[0109] Ambient temperature, humidity, and wind speed data affect the battery's temperature changes and heat dissipation efficiency during charging, thus affecting charging efficiency.

[0110] A5, obtains charging specification information, current battery power data, and current battery temperature data of parked vehicles;

[0111] Charging specifications information refers to the charging-related specifications of the parked vehicles, such as the battery rated capacity and maximum DC charging power.

[0112] The current battery power data refers to the remaining battery level of the vehicle's onboard battery.

[0113] The current battery temperature data refers to the current battery temperature of the vehicle's onboard battery while it is parked.

[0114] A6 determines the corresponding DC charging time and AC charging time based on the estimated parking time, ambient temperature data, ambient humidity data, ambient wind speed data, charging specification information, current battery power data, and current battery temperature data.

[0115] DC charging duration is the duration during which the vehicle is DC charged while parked.

[0116] AC charging duration refers to the duration during which the vehicle is AC charged while parked.

[0117] Among them, the sum of DC charging time and AC charging time is less than or equal to the estimated parking time;

[0118] Based on the estimated parking time, ambient temperature data, ambient humidity data, ambient wind speed data, charging specifications, current battery level data, and current battery temperature data, the corresponding DC charging time and AC charging time can be calculated using a preset algorithm. For example, different constraints can be set for each parameter to build a corresponding algorithm model, and then solve for the optimal time allocation strategy; or a corresponding recognition model can be trained based on historical data to generate the corresponding DC charging time and AC charging time.

[0119] A7. Charge the parked vehicle using preset DC charging mode and preset AC charging mode according to the DC charging time and AC charging time respectively.

[0120] The DC / AC charging pile charges the parked vehicle with DC charging based on the DC charging duration and with AC charging based on the AC charging duration.

[0121] The vehicle can be charged first using a DC charging model to quickly increase the battery capacity, and then switched to AC charging after a certain capacity is reached to extend the battery's lifespan.

[0122] Through the above steps, the DC / AC multimodal adaptive allocation method for the charging pile can integrate multi-dimensional data such as charging area information, meteorological data, and vehicle information, use a pre-trained model to estimate the corresponding estimated parking time, and combine real-time environmental parameters and vehicle battery status to intelligently allocate DC and AC charging time, so as to maximize charging efficiency and optimize battery protection.

[0123] Furthermore, the DC / AC multimodal adaptive allocation method for the charging pile further includes the following steps for obtaining vehicle type information:

[0124] B1, acquire vehicle image data of the parked vehicle;

[0125] The vehicle image data refers to images of parked vehicles, which can be obtained through cameras installed near AC / DC charging stations.

[0126] B2, determine the corresponding vehicle color information based on vehicle image data;

[0127] The vehicle color information refers to the color information of the parked vehicle, which can be identified and determined through the corresponding image recognition algorithm.

[0128] B3, attempting to obtain the VIN code data of the parked vehicle;

[0129] The VIN code data is the VIN code of the parked vehicle, which can generally be obtained through communication between the charging head and the charging vehicle.

[0130] B4. If the VIN code data is successfully obtained, the corresponding vehicle type information is determined according to the VIN code data through the preset VIN code lookup table, and the vehicle color information is added to the vehicle type information.

[0131] The VIN code lookup table is a pre-set lookup table used to determine the corresponding vehicle information based on the VIN code.

[0132] B5. If the VIN code data acquisition fails, the corresponding vehicle type identification information is generated based on the vehicle image data of the parked vehicle using a preset vehicle identification algorithm.

[0133] The vehicle recognition algorithm is a pre-set algorithm that can predict and identify the brand, type, model, etc. of a vehicle based on vehicle image data.

[0134] Vehicle type identification information is information about the vehicle type determined based on vehicle image data.

[0135] B6, generates vehicle type information by combining vehicle color information and vehicle type identification information;

[0136] Add vehicle color information to vehicle type recognition information to generate vehicle type information.

[0137] Through the above steps, the DC / AC multimodal adaptive allocation method for charging piles adopts a dual identification mechanism. It prioritizes obtaining accurate vehicle type information by querying the VIN code database. When the VIN code acquisition fails, it automatically switches to a backup scheme based on vehicle image recognition, ensuring the reliability and fault tolerance of vehicle identification. At the same time, vehicle color information is integrated into the vehicle type information as an important supplementary identifier, enriching the vehicle type information and providing a more comprehensive data foundation for subsequent charging strategy formulation.

[0138] Further, step A3 includes the following steps:

[0139] A301 determines the corresponding area type code value based on the charging area information and a preset area type lookup table;

[0140] The region type lookup table is a pre-defined lookup table;

[0141] The area type code value is a numerical encoding of the charging area information, which quantifies the charging area information to facilitate subsequent processing steps.

[0142] A302, determine the corresponding meteorological time series data based on meteorological forecast data and preset meteorological time series;

[0143] Meteorological time series are pre-set time series used to acquire corresponding data;

[0144] Meteorological time series data are the corresponding data obtained from meteorological time series and meteorological forecast data;

[0145] For example, if the current time is set as T, and the range of the meteorological time series is the next 2 hours with an interval of 15 minutes, then the corresponding meteorological time series can be obtained as [T+15min, T+30min, T+45min, …, T+90min, T+105min, T+120min]. Then, based on the meteorological time series, the temperature, humidity, wind speed and other data of each time are obtained from the meteorological forecast data to form meteorological time series data.

[0146] A303 generates corresponding vehicle type word vector data based on vehicle type information using a preset word vector algorithm;

[0147] The word vector algorithm is a pre-defined text processing algorithm used to vectorize the text content in vehicle type information;

[0148] Vehicle type word vector data consists of word vectors corresponding to vehicle type information.

[0149] A304 generates comprehensive vehicle environment data by combining regional type code values, meteorological time series data, parking start time and vehicle type word vector data.

[0150] The comprehensive vehicle environment data is a collection of data including regional type code values, meteorological time series data, parking start time, and vehicle type word vector data.

[0151] A305 generates corresponding vehicle environment feature data based on comprehensive vehicle environment data using a preset feature extraction algorithm.

[0152] The feature extraction algorithm is a pre-defined algorithm used to extract feature data from the corresponding data;

[0153] Vehicle environmental feature data refers to the feature data corresponding to the comprehensive vehicle environmental data.

[0154] A306, Based on the vehicle environmental characteristic data, the corresponding estimated parking time is generated through the parking time prediction model;

[0155] Input vehicle environmental characteristic data into the parking duration prediction model to generate the corresponding predicted parking duration.

[0156] Through the above steps, the DC / AC multimodal adaptive allocation method for charging piles can standardize and vectorize multidimensional heterogeneous data such as regional type, meteorological conditions, parking time, and vehicle type through systematic data preprocessing and feature engineering, thereby constructing a comprehensive vehicle environment data model. Furthermore, by using feature extraction algorithms to mine the inherent correlations between data, it provides high-quality input features for machine learning models, which can improve the accuracy and stability of parking time prediction and provide reliable data support for subsequent charging time allocation.

[0157] Further, step A6 includes the following steps:

[0158] A601 calculates the corresponding effective charging time by multiplying the estimated parking time and the preset effective charging time coefficient.

[0159] The effective charging time coefficient is a preset coefficient used to calculate the corresponding effective charging time;

[0160] The effective charging time is the estimated time available for charging within the estimated parking time. Because there may be a certain buffer time during the charging process depending on various factors, the effective charging time coefficient also needs to take into account the accuracy of the estimated parking time in order to ensure charging efficiency.

[0161] For example, setting the effective charging time coefficient to 0.9 means that 90% of the estimated parking time can be used for charging.

[0162] A602, determine the maximum DC charging power accepted by the vehicle based on the charging specification information, obtain the maximum DC output power of the AC charging pile, and determine the minimum value between the maximum DC charging power accepted by the vehicle and the maximum DC output power of the charging pile and define it as the DC charging base power.

[0163] The maximum power that a vehicle can receive when DC charging is performed is the maximum power that the parked vehicle can withstand.

[0164] The maximum DC output power of a charging pile is the maximum power that the AC charging pile can output when performing DC charging.

[0165] The DC charging base power is the minimum of the vehicle's maximum DC charging power and the charging pile's maximum DC output power.

[0166] A603 calculates the corresponding environmental correction factor based on ambient temperature data, ambient humidity data, and ambient wind speed data using a preset environmental correction factor algorithm.

[0167] The environmental correction factor algorithm is a pre-defined algorithm used to calculate the corresponding environmental correction factor based on environmental temperature data, environmental humidity data, and environmental wind speed data.

[0168] The environmental correction factor is a correction factor calculated based on environmental temperature data, environmental humidity data, and environmental wind speed data.

[0169] For example, the environmental correction factor can be calculated using the following method:

[0170] Optimal temperature range (15-25°C), ambient temperature coefficient = 1.0;

[0171] For the low-temperature range (0-15°C), the ambient temperature coefficient = 0.7 + 0.3 × (current temperature / 15);

[0172] In the high-temperature range (25-40°C), the ambient temperature coefficient is 1.0 - 0.4 × ((current temperature - 25) / 15).

[0173] Extreme temperatures (<0°C or >40°C): Ambient temperature coefficient = 0.5;

[0174] Normal humidity (30%-70%), ambient humidity coefficient = 1.0;

[0175] Low humidity (<30%), ambient humidity coefficient = 0.95 (static electricity risk);

[0176] High humidity (>70%), ambient humidity coefficient = 0.85 (equipment protection);

[0177] Extremely high humidity (>90%), ambient humidity coefficient = 0.7 (for safety reasons);

[0178] Light breeze (0-2 m / s), ambient wind speed coefficient = 1.0;

[0179] Moderate wind speed (2-8 m / s), ambient wind speed coefficient = 1.1 (favorable for heat dissipation);

[0180] Strong winds (8-15 m / s), ambient wind speed coefficient = 1.0 (good heat dissipation but affected by equipment);

[0181] Extremely strong winds (>15m / s), ambient wind speed coefficient = 0.8 (for equipment safety considerations);

[0182] Finally, the corresponding environmental correction coefficient can be calculated by weighting the environmental temperature coefficient, environmental humidity coefficient, and environmental wind speed coefficient.

[0183] A604 calculates the corresponding target threshold DC charging amount based on the current battery power data and the preset target power threshold.

[0184] The target power threshold is a pre-set initial charging target power, such as 80% power, 70%, 60%, etc., which can be manually set according to needs or actual experience.

[0185] The target threshold DC charging amount is the difference between the amount of electricity corresponding to the target energy threshold and the current battery level. In other words, the parked vehicle needs to be charged with the target threshold DC charging amount to reach the target energy threshold.

[0186] A605, calculates the corresponding target charge DC charging time based on the target threshold DC charging amount and DC charging base power;

[0187] The target charge DC charging time is the charging time required to reach the target charge threshold in DC charging mode, which can be determined by quotienting the target threshold DC charging amount and the DC charging base power.

[0188] A606, the corresponding DC charging ratio coefficient is calculated and determined based on the environmental correction factor, the current battery temperature data and the preset DC charging time base ratio coefficient.

[0189] The DC charging time base ratio coefficient is the pre-set ratio of DC charging time to effective charging time, for example, 0.7;

[0190] The DC charging ratio coefficient is the actual coefficient adjusted based on the DC charging duration ratio coefficient, environmental correction coefficient, and current battery temperature data.

[0191] For example, the corresponding battery temperature coefficient is determined based on the current battery temperature data, and then the corresponding correction coefficient is calculated by combining the environmental correction coefficient. The DC charging time base ratio coefficient is then corrected to obtain the DC charging ratio coefficient.

[0192] A607, calculate the corresponding maximum DC charging time by multiplying the effective charging time and the DC charging ratio coefficient;

[0193] The maximum DC charging time is the maximum duration that can be used for DC charging within the effective charging time.

[0194] A608, the minimum value between the target DC charging time and the maximum DC charging time is defined as the DC charging time;

[0195] The DC charging time is the minimum value between the target DC charging time and the maximum DC charging time. Since the parking time of the parked vehicle is sufficient to charge to the target power threshold, the minimum value of the two is selected as the actual DC charging time.

[0196] A609, the AC charging time is determined by the difference between the effective charging time and the DC charging time;

[0197] Subtracting the DC charging time from the effective charging time yields the AC charging time. AC charging can be performed after DC charging, which ensures both charging efficiency and battery life.

[0198] Through the above steps, the DC / AC multimodal adaptive allocation method for charging piles can achieve a dynamic balance between charging efficiency and battery protection by comprehensively considering multiple constraints such as vehicle charging capacity, charging pile output limitations, environmental factor correction, and battery safety protection. By adopting a dual constraint mechanism (target power demand and environmental safety constraints) to determine the optimal DC charging time, the remaining time is automatically allocated for AC charging. This ensures that the demand for fast charging is met while avoiding damage to the battery caused by excessive DC charging. It realizes intelligent, safe, and personalized charging strategies, significantly improving the overall performance of the charging system and the user experience.

[0199] Further, step A7 includes the following steps:

[0200] A701, defines DC charging duration as the remaining DC charging duration;

[0201] The remaining DC charging time is the remaining time that can be used for DC charging. At the start of charging, the remaining DC charging time is the DC charging duration. As DC charging continues, the remaining DC charging time will gradually decrease until it reaches 0, at which point DC charging will stop.

[0202] A702, charge the parked vehicle in DC charging mode according to the remaining DC charging time, and record the DC charging execution time;

[0203] The DC charging execution duration is the execution duration of the DC charging mode, used to record the length of time that DC charging has consumed.

[0204] In DC charging mode, the A703 obtains battery charging temperature window data according to a preset temperature monitoring window.

[0205] The temperature monitoring window is a pre-set time window used to collect battery temperature data over a period of time. For example, the temperature monitoring window can be the time window corresponding to the past 5 minutes.

[0206] The battery charging temperature time window data is the battery temperature data of parked vehicles obtained within the temperature monitoring time window.

[0207] A704 determines the current charging battery temperature and battery temperature trend slope based on battery charging temperature time window data.

[0208] The current charging battery temperature is the temperature corresponding to the current battery, which can be the average, maximum, or weighted average of the battery charging temperature time window data, etc.

[0209] The slope of the battery temperature trend is the slope of temperature change in the battery charging temperature time window data. The corresponding slope can be obtained by performing linear regression based on the temperature data.

[0210] A705, If the current charging battery temperature is greater than or equal to the preset DC charging battery temperature warning threshold, and the battery temperature trend slope is greater than or equal to the preset temperature slope warning threshold, then proceed to step A707.

[0211] The DC charging battery temperature warning threshold is a preset reference value used to determine the current charging battery temperature.

[0212] The temperature slope warning threshold is a preset reference value used to determine the magnitude of the battery temperature trend slope.

[0213] When the current charging battery temperature is greater than the DC charging battery temperature warning threshold, and the battery temperature trend slope is greater than the temperature slope warning threshold, it indicates that DC charging may cause the battery temperature to be too high, and intervention and adjustment are required.

[0214] A706, If the current charging battery temperature is greater than or equal to the preset DC charging battery temperature danger threshold, then proceed to step A707.

[0215] The dangerous temperature threshold for DC charging batteries is a preset reference value used to determine whether the current charging battery temperature is too high.

[0216] If the current charging battery temperature exceeds the dangerous threshold for DC charging battery temperature, it indicates that the battery temperature is too high and intervention is required.

[0217] A707 updates the remaining DC charging time by decrementing it based on the DC charging execution time, and switches to AC charging mode to charge the parked vehicle.

[0218] The new remaining DC charging time is obtained by subtracting the already executed DC charging time from the remaining DC charging time, and then switching to AC charging mode.

[0219] A708, in AC charging mode, obtains battery charging temperature window data based on temperature monitoring window and determines the corresponding current charging battery temperature and battery temperature trend slope.

[0220] In AC charging mode, the current charging battery temperature and the battery temperature trend slope are collected and calculated.

[0221] A709, If the current charging battery temperature is less than or equal to the preset DC charging battery temperature switching threshold, and the battery temperature trend slope is less than or equal to the preset temperature slope switching threshold, and the remaining DC charging time is greater than zero, then execute step A702.

[0222] The DC charging battery temperature switching threshold is a preset reference value used to determine the current charging battery temperature.

[0223] When the current charging battery temperature is lower than the DC charging battery temperature switching threshold, and the battery temperature trend slope is less than or equal to the temperature slope switching threshold, it indicates that the battery charging temperature is low and tends to be stable. It can be switched back to DC mode for charging to ensure charging efficiency.

[0224] A710, if the remaining DC charging time is zero, switch to AC charging mode to charge the parked vehicle until the current battery power data is greater than or equal to the preset maximum power threshold.

[0225] The maximum charge threshold is the maximum charge that the battery can be charged to, for example, the maximum charge threshold is usually set to 95% of the battery's maximum capacity, that is, 95% of the battery capacity.

[0226] When the remaining DC charging time is zero, it means that the DC charging time has been used up. At this time, the battery has usually been charged to a high level. In order to protect the battery, it is necessary to switch to AC charging mode.

[0227] Through the above steps, the DC / AC multimodal adaptive matching method of the charging pile can achieve seamless adaptive switching between DC and AC charging modes by continuously monitoring the battery temperature change trend and battery temperature value, setting multiple safety thresholds and judgment logic. It can not only protect the battery safety in time when the battery temperature is abnormal, but also automatically restore efficient DC charging after the temperature returns to normal. It maximizes the advantages of DC fast charging while ensuring the safety of the charging process, and achieves a balance between charging efficiency and battery life protection.

[0228] Furthermore, the DC / AC multimodal adaptive allocation method for the charging pile further includes the following steps:

[0229] B1, when charging the parked vehicle in DC charging mode, record the corresponding DC time period data;

[0230] The DC period data is a dataset of each DC charging period during which the parked vehicle is being charged.

[0231] B2, determine the actual DC charging duration based on DC period data statistics;

[0232] The actual DC charging duration is the total actual duration of DC charging when the parked vehicle is being charged, which can be determined based on the duration statistics of each time period in the DC time period data.

[0233] B3, when charging the parked vehicle in AC charging mode, record the corresponding AC time period data;

[0234] The AC charging time data is a dataset of each time period during which the parked vehicle performs AC charging.

[0235] B4. Determine the actual AC charging time based on AC time period data statistics;

[0236] The actual AC charging duration is the total actual duration of AC charging when the parked vehicle is being charged, which can be determined based on the duration statistics of each time period in the AC time period data.

[0237] B5 calculates the corresponding vehicle charging cost based on the actual DC charging duration, the preset DC charging unit price, the actual AC charging duration, and the preset AC charging unit price.

[0238] The unit price for DC charging is the unit price for the preset duration of DC charging mode;

[0239] The AC charging unit price is the unit price for the preset AC charging mode duration;

[0240] The vehicle charging fee is the cost incurred for the entire charging process of a parked vehicle.

[0241] Through the above steps, the DC / AC multimodal adaptive allocation method for charging piles can accurately calculate costs by recording and statistically analyzing the actual execution time of DC and AC charging modes in real time and combining them with their respective billing prices. This achieves the effective implementation of differentiated pricing strategies, ensuring not only the accuracy and transparency of billing but also reflecting the reasonable pricing of different cost structures for DC fast charging and AC slow charging. It provides users with clear cost details, while also providing charging operators with flexible business model support and improving the commercial operation efficiency of charging services.

[0242] Furthermore, the DC / AC multimodal adaptive allocation method for the charging pile further includes the following steps:

[0243] C1, based on a preset statistical period, obtains the actual parking time and estimated parking time of each parked vehicle from a preset historical vehicle charging database;

[0244] The statistical period is a pre-defined statistical time range, which determines the data within that range; for example, the statistical period can be set to one month.

[0245] The historical vehicle charging database is a pre-set database that stores historical data on past vehicle parking and charging.

[0246] The actual parking duration is the actual duration of a single parking session for the vehicle.

[0247] C2, calculate the corresponding effective parking time ratio by quoting the actual parking time and the estimated parking time of the parked vehicle;

[0248] The effective parking time ratio is the quotient of the actual parking time and the estimated parking time, used to reflect the accuracy of the estimated parking time in this parking session.

[0249] C3, if the effective parking time ratio of the parked vehicle is greater than 1, then the effective parking time ratio is assigned to 1.

[0250] That is, when the actual parking time is greater than or equal to the estimated parking time, the effective parking time ratio is assigned as 1.

[0251] C4, based on the proportion of effective parking time of all parked vehicles within the statistical period, determines the corresponding typical parking time proportion and defines it as the effective charging time coefficient.

[0252] The typical parking duration ratio is a typical value determined based on the proportion of effective parking duration of all parked vehicles within the statistical period. It can be an average, weighted average, or other available statistical value.

[0253] Through the above steps, the DC / AC multimodal adaptive allocation method of the charging pile can automatically adjust the effective charging time coefficient by continuously collecting and analyzing the deviation between the actual parking time and the estimated parking time, thereby realizing intelligent iterative optimization of system parameters. It can not only continuously improve the estimation accuracy based on actual operating data, but also ensure the stability and accuracy of charging allocation in long-term operation.

[0254] refer to Figure 2 The present invention also provides a DC / AC multimodal adaptive dispatching system for charging piles, comprising:

[0255] Image acquisition module 10;

[0256] Environmental monitoring module 20;

[0257] 30-speed AC charging module;

[0258] Processing control module 40;

[0259] The image acquisition module 10, the environment detection module 20, and the DC / AC charging module 30 are respectively connected to the processing and control module 40.

[0260] The environmental detection module 20 includes a temperature detection module 21, a humidity detection module 22, and a wind speed detection module 23. The temperature detection module 21, the humidity detection module 22, and the wind speed detection module 23 are respectively connected to the processing and control module 40.

[0261] The DC / AC charging module 30 includes a DC charging module 31, an AC charging module 32, a vehicle connection module 33, and a communication module 34. The DC charging module 31, the AC charging module 32, and the communication module 34 are electrically connected to the vehicle connection module 33, and the communication module 34 is communicatively connected to the processing and control module 40.

[0262] The image acquisition module 10 is mainly used to acquire image data of parked vehicles.

[0263] The environmental detection module 20 is mainly used to detect various environmental factors around the AC / DC charging module 30, namely, various environmental factors around the parked vehicle.

[0264] The temperature detection module 21 is mainly used to detect the ambient temperature data around the AC / DC charging module 30;

[0265] The humidity detection module 22 is mainly used to detect the humidity data around the AC / DC charging module 30;

[0266] The wind speed detection module 23 is mainly used to detect the wind speed data around the AC / DC charging module 30.

[0267] The DC / AC charging module 30 is mainly used to charge parked vehicles and can switch between DC charging and AC charging as needed.

[0268] The DC charging module 31 is mainly used for DC charging of parked vehicles;

[0269] The AC charging module 32 is mainly used for AC charging of parked vehicles;

[0270] The vehicle connection module 33 is mainly used for electrical connection with parked vehicles;

[0271] The communication module 34 is mainly used for data communication with parked vehicles.

[0272] The processing and control module 40 is mainly used to acquire and process data from each module and control each module.

[0273] The DC / AC multimodal adaptive allocation system of the charging pile further includes an adaptive charging strategy, comprising the following steps:

[0274] D1, obtain the charging area information and weather forecast data of the location of the AC / DC charging module 30;

[0275] D2, when a pre-defined parked vehicle connects to the AC / DC charging module 30, obtains the corresponding parking start time and vehicle type information;

[0276] D3, the processing control module 40 generates the corresponding estimated parking time based on the charging area information, meteorological forecast data, parking start time and vehicle type information through a pre-trained parking time estimation model;

[0277] D4, the environmental detection module 20 acquires the ambient temperature data, ambient humidity data and ambient wind speed data of the location of the AC / DC charging pile;

[0278] D5, obtains the charging specification information, current battery power data and current battery temperature data of the parked vehicle through the AC / DC charging module 30;

[0279] D6, the processing control module 40 determines the corresponding DC charging time and AC charging time based on the estimated parking time, ambient temperature data, ambient humidity data, ambient wind speed data, charging specification information, current battery power data and current battery temperature data;

[0280] D7, the DC / AC charging module 30 charges the parked vehicle using preset DC charging mode and preset AC charging mode according to the DC charging time and AC charging time, respectively.

[0281] Through the above technical solutions, the DC / AC multimodal adaptive allocation system of the charging pile can integrate multi-dimensional data such as charging area information, meteorological data, and vehicle information, use a pre-trained model to estimate the corresponding estimated parking time, and combine real-time environmental parameters and vehicle battery status to intelligently allocate DC and AC charging time, so as to maximize charging efficiency and optimize battery protection.

[0282] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. A DC / AC multimodal adaptive allocation method for charging piles, characterized in that, Includes the following steps: A1, obtain the charging area information and weather forecast data of the preset location of AC / DC charging piles; A2, when a pre-defined parked vehicle connects to the AC / DC charging pile, obtain the corresponding parking start time and vehicle type information; A3 generates the corresponding estimated parking duration based on charging area information, weather forecast data, parking start time and vehicle type information through a pre-trained parking duration estimation model. A4, obtain the ambient temperature data, ambient humidity data and ambient wind speed data of the location of the AC / DC charging pile; A5, obtains charging specification information, current battery power data, and current battery temperature data of parked vehicles; A6 determines the corresponding DC charging time and AC charging time based on the estimated parking time, ambient temperature data, ambient humidity data, ambient wind speed data, charging specification information, current battery power data, and current battery temperature data. A7. Charge the parked vehicle using preset DC charging mode and preset AC charging mode according to the DC charging time and AC charging time respectively. Step A7 includes the following steps: A701, defines DC charging duration as the remaining DC charging duration; A702, charge the parked vehicle in DC charging mode according to the remaining DC charging time, and record the DC charging execution time; In DC charging mode, the A703 obtains battery charging temperature window data according to a preset temperature monitoring window. A704 determines the current charging battery temperature and battery temperature trend slope based on battery charging temperature time window data. A705, If the current charging battery temperature is greater than or equal to the preset DC charging battery temperature warning threshold, and the battery temperature trend slope is greater than or equal to the preset temperature slope warning threshold, then proceed to step A707. A706, If the current charging battery temperature is greater than or equal to the preset DC charging battery temperature danger threshold, then proceed to step A707. A707 updates the remaining DC charging time by decrementing it based on the DC charging execution time, and switches to AC charging mode to charge the parked vehicle. A708, in AC charging mode, obtains battery charging temperature window data based on temperature monitoring window and determines the corresponding current charging battery temperature and battery temperature trend slope. A709, If the current charging battery temperature is less than or equal to the preset DC charging battery temperature switching threshold, and the battery temperature trend slope is less than or equal to the preset temperature slope switching threshold, and the remaining DC charging time is greater than zero, then execute step A702. A710: If the remaining DC charging time is zero, switch to AC charging mode to charge the parked vehicle until the current battery power data is greater than or equal to the preset maximum power threshold.

2. The DC / AC multimodal adaptive allocation method for charging piles according to claim 1, characterized in that, The following steps are further included to obtain vehicle type information: B1, acquire vehicle image data of the parked vehicle; B2, determine the corresponding vehicle color information based on vehicle image data; B3, attempting to obtain the VIN code data of the parked vehicle; B4. If the VIN code data is successfully obtained, the corresponding vehicle type information is determined according to the VIN code data through the preset VIN code lookup table, and the vehicle color information is added to the vehicle type information. B5. If the VIN code data acquisition fails, the corresponding vehicle type identification information is generated based on the vehicle image data of the parked vehicle using a preset vehicle identification algorithm. B6 generates vehicle type information by combining vehicle color information and vehicle type identification information.

3. The DC / AC multimodal adaptive allocation method for charging piles according to claim 2, characterized in that, Step A3 includes the following steps: A301 determines the corresponding area type code value based on the charging area information and a preset area type lookup table; A302, determine the corresponding meteorological time series data based on meteorological forecast data and preset meteorological time series; A303 generates corresponding vehicle type word vector data based on vehicle type information using a preset word vector algorithm; A304 generates comprehensive vehicle environment data by combining regional type code values, meteorological time series data, parking start time and vehicle type word vector data. A305 generates corresponding vehicle environment feature data based on comprehensive vehicle environment data using a preset feature extraction algorithm. A306, based on the vehicle environmental characteristic data, generates the corresponding estimated parking duration through the parking duration prediction model.

4. The DC / AC multimodal adaptive allocation method for charging piles according to claim 3, characterized in that, Step A6 includes the following steps: A601 calculates the corresponding effective charging time by multiplying the estimated parking time and the preset effective charging time coefficient. A602, determine the maximum DC charging power accepted by the vehicle based on the charging specification information, obtain the maximum DC output power of the AC charging pile, and determine the minimum value between the maximum DC charging power accepted by the vehicle and the maximum DC output power of the charging pile and define it as the DC charging base power. A603 calculates the corresponding environmental correction factor based on ambient temperature data, ambient humidity data, and ambient wind speed data using a preset environmental correction factor algorithm. A604 calculates the corresponding target threshold DC charging amount based on the current battery power data and the preset target power threshold. A605, calculates the corresponding target charge DC charging time based on the target threshold DC charging amount and DC charging base power; A606, the corresponding DC charging ratio coefficient is calculated and determined based on the environmental correction factor, the current battery temperature data and the preset DC charging time base ratio coefficient. A607, calculate the corresponding maximum DC charging time by multiplying the effective charging time and the DC charging ratio coefficient; A608, the minimum value between the target DC charging time and the maximum DC charging time is defined as the DC charging time; A609 determines the AC charging time by calculating the difference between the effective charging time and the DC charging time.

5. The DC / AC multimodal adaptive allocation method for charging piles according to claim 4, characterized in that, Further steps include: B1, when charging the parked vehicle in DC charging mode, record the corresponding DC time period data; B2, determine the actual DC charging duration based on DC period data statistics; B3, when charging the parked vehicle in AC charging mode, record the corresponding AC time period data; B4. Determine the actual AC charging time based on AC time period data statistics; B5 calculates the corresponding vehicle charging cost based on the actual DC charging duration, the preset DC charging unit price, the actual AC charging duration, and the preset AC charging unit price.

6. The DC / AC multimodal adaptive allocation method for charging piles according to claim 5, characterized in that, Further steps include: C1, based on a preset statistical period, obtains the actual parking time and estimated parking time of each parked vehicle from a preset historical vehicle charging database; C2, calculate the corresponding effective parking time ratio by quoting the actual parking time and the estimated parking time of the parked vehicle; C3, if the effective parking time ratio of the parked vehicle is greater than 1, then the effective parking time ratio is assigned to 1. C4, based on the proportion of effective parking time of all parked vehicles within the statistical period, determines the corresponding typical parking time proportion and defines it as the effective charging time coefficient.

7. A DC / AC multimodal adaptive allocation system for charging piles, used to implement the DC / AC multimodal adaptive allocation method for charging piles as described in any one of claims 1-6, characterized in that, include: Image acquisition module; Environmental monitoring module; AC / DC charging module; Processing control module; The image acquisition module, the environment detection module, and the DC / AC charging module are respectively connected to the processing and control module. The environmental detection module includes a temperature detection module, a humidity detection module, and a wind speed detection module, and the temperature detection module, the humidity detection module, and the wind speed detection module are respectively connected to the processing and control module. The DC / AC charging module includes a DC charging module, an AC charging module, a vehicle connection module, and a communication module. The DC charging module, the AC charging module, and the communication module are electrically connected to the vehicle connection module, and the communication module is communicatively connected to the processing and control module. The DC / AC multimodal adaptive allocation system of the charging pile further includes an adaptive charging strategy, comprising the following steps: D1, obtain the charging area information and weather forecast data of the location of the AC / DC charging module; D2, when a pre-defined parked vehicle connects to the AC / DC charging module, obtains the corresponding parking start time and vehicle type information; D3, the processing and control module generates the corresponding estimated parking time based on the charging area information, meteorological forecast data, parking start time and vehicle type information through a pre-trained parking time estimation model; D4, obtains ambient temperature data, ambient humidity data and ambient wind speed data of the location of the DC / AC charging module through the environmental detection module; D5, obtains the charging specification information, current battery power data and current battery temperature data of the parked vehicle through the AC / DC charging module; D6, the processing and control module determines the corresponding DC charging time and AC charging time based on the estimated parking time, ambient temperature data, ambient humidity data, ambient wind speed data, charging specification information, current battery power data and current battery temperature data; D7, the DC / AC charging module charges the parked vehicle using preset DC charging mode and preset AC charging mode according to the DC charging time and AC charging time, respectively.

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