Priority-based charging pile power dynamic distribution system and method

Abstract

The invention discloses a priority-based charging pile power dynamic distribution system and method, and relates to the technical field of electric vehicle charging. Comprising a vehicle information acquisition module, a charging pile state monitoring module, a priority evaluation module, a power distribution module and a user interaction module, wherein the vehicle information acquisition module is used for acquiring a current SOC value, a target SOC value, vehicle demand power, a vehicle type, a user type and a payment mode of a vehicle in real time; the charging pile state monitoring module is used for monitoring the number of modules, the number of used modules and the number of remaining modules of the charging pile in real time. According to the priority-based charging pile power dynamic distribution system and method provided by the invention, the charging priorities of the vehicles are evaluated, the charging pile modules are reasonably distributed, and meanwhile, it is ensured that the vehicles with small demands occupy at least one power module, so that the problems that the vehicles with small demands occupy too many modules and the vehicle modules with large demands are not enough are solved; and the use efficiency and the user experience of the charging pile are improved.

Description

Technical Field

[0001] This invention relates to the field of electric vehicle charging technology, specifically a priority-based dynamic power allocation system and method for charging piles. Background Technology

[0002] With the increasing popularity of electric vehicles, the demand for charging stations is also growing. Existing charging stations, when multiple vehicles are charging simultaneously, often determine their output power based on the number of DC output modules allocated for scheduling. This results in vehicles with lower demand using too many modules, while vehicles with higher demand lack sufficient modules, impacting the efficiency of the charging stations and the user experience. Therefore, a system and method are needed that can rationally allocate charging station modules according to the actual needs of vehicles.

[0003] This invention aims to provide a priority-based dynamic power allocation system and method for charging piles. By evaluating the charging priority of vehicles, the system rationally allocates charging pile modules, while ensuring that vehicles with low demand occupy at least one power module. This solves the problem of vehicles with low demand occupying too many modules, while vehicles with high demand do not have enough modules, thereby improving the utilization efficiency of charging piles and the user experience.

[0004] Therefore, a priority-based dynamic power allocation system and method for charging piles are proposed here. Summary of the Invention

[0005] Technical problems to be solved The purpose of this invention is to overcome the shortcomings of the prior art and provide a priority-based dynamic power allocation system and method for charging piles, thereby improving overall charging efficiency, shortening charging time, and enhancing user experience.

[0006] Technical solution To achieve the above objectives, the present invention provides the following technical solution: a priority-based dynamic power allocation system for charging piles, characterized in that it includes a vehicle information acquisition module, a charging pile status monitoring module, a priority evaluation module, a power allocation module, and a user interaction module. The vehicle information collection module is used to collect the vehicle's current SOC value, target SOC value, vehicle power demand, vehicle type, user type, and payment mode in real time.

[0007] The charging pile status monitoring module is used to monitor the number of modules, the number of modules used, and the number of modules remaining in the charging pile in real time.

[0008] Priority assessment module: Based on the data provided by the vehicle information collection module and the charging pile status monitoring module, assess the charging priority of each vehicle.

[0009] Power allocation module: Based on the evaluation results of the priority evaluation module, dynamically allocates charging pile modules to meet the charging needs of vehicles.

[0010] User interaction module: Used to display the current charging priority, estimated charging time and module allocation to the user, and to provide user guidance functions.

[0011] Preferably, the vehicle information collection module is able to identify and adapt to different types of electric vehicles and their specific needs.

[0012] Preferably, the priority evaluation module uses a comprehensive scoring mechanism to calculate the priority score for each vehicle, which is based on factors such as current SOC, required power, vehicle type, user type, and payment mode.

[0013] Preferably, the vehicle types include different types of vehicles such as private cars, taxis, buses, and logistics vehicles.

[0014] Preferably, the power allocation module can adjust the charging priority and module allocation of each vehicle in real time during the charging process to cope with resource changes.

[0015] Preferably, the system also includes an exception handling mechanism, which immediately releases module resources for use by subsequent vehicles in the queue when a vehicle prematurely pulls out its gun.

[0016] A priority-based dynamic power allocation method for charging piles includes the following steps: Vehicle information collection: Real-time collection of information such as the vehicle's current SOC value, target SOC value, vehicle power demand, vehicle type, user type, and payment mode.

[0017] Charging pile status monitoring: Real-time monitoring of information such as the number of modules in the charging pile, the number of modules used, and the number of modules remaining.

[0018] Priority assessment: Calculate the required charging power for the vehicle based on its current SOC and target SOC, and assess the charging priority of each vehicle by combining the vehicle's power demand and the number of remaining modules in the charging station.

[0019] Power allocation: Based on priority evaluation results, charging station modules are dynamically allocated. Vehicles with higher priority are allocated more modules, while vehicles with lower priority are allocated fewer modules. However, vehicles with low demand will occupy at least one power module.

[0020] Real-time adjustment: During the charging process, the charging status of the vehicle and the resource changes of the charging pile are monitored in real time, and the charging priority and module allocation of the vehicle are dynamically adjusted.

[0021] User interaction: The charging station displays the current charging priority, estimated charging time, and module allocation information on its screen or mobile application, guiding users to choose the appropriate charging time.

[0022] Preferably, in the priority evaluation step, the priority score of each vehicle is determined by calculating the formula Score_i=w1×Preq_i+w2×(1-SOC_i)+w3×Vehicle_i+w4×User_i+w5×Mode_i.

[0023] Preferably, in the real-time adjustment step of step 5, the system dynamically adjusts the weight coefficients of each parameter according to different time periods of the day or special events.

[0024] Preferably, in the power allocation step of step 4, a constraint-based linear programming model is used, which aims to maximize the sum of the satisfaction scores of all vehicles while complying with constraints such as the maximum output power limit of a single pile and the allocation of at least one module to each vehicle.

[0025] Power demand ranking and priority determination Step 1: Introduce a comprehensive scoring mechanism: For each connected vehicle, a comprehensive score is calculated based on its current SOC, power demand vehicle type, user type, payment mode, etc.

[0026] The calculation formula is: Score_i = w1 × Preq_i + w2 × (1 - SOC_i) + w3 × Vehicle_i + w4 × User_i + w5 × Mode_i, where Preq_i is the power demand of the i-th vehicle, SOC_i is its current state of charge, Vehicle_i is its vehicle type (e.g., private car, taxi, bus, logistics vehicle), User_i is its user category (e.g., regular user, VIP user, reservation user), and Mode_i is its payment method (e.g., prepaid, postpaid, membership card payment). w1, w2, w3, w4, and w5 are the weighting coefficients for these parameters, which can be adjusted according to actual conditions. The purpose of using 1 - SOC_i is to give higher priority to vehicles with lower battery levels.

[0027] Step 2: Dynamically adjust the weights: The weights of each parameter can be dynamically adjusted based on different times of day or special events (such as holidays). For example, during off-peak hours, the value of w2 can be increased, thus favoring vehicles that are close to depleted but still need some time to charge; while during peak hours, the weight of w2 can be appropriately reduced to ensure that high-power-demand vehicles can obtain the required power as quickly as possible.

[0028] Power Allocation Algorithm Constraint-based linear programming models: The power allocation problem is solved by constructing a linear programming model. The objective function aims to maximize the sum of satisfaction scores for all vehicles, while adhering to the following constraints: Maximum output power limit for a single pile; Each vehicle is assigned at least one module; Maximum output power limit for each charging gun; The actual charging power of a vehicle must not exceed its required power. For each vehicle's SOC, power is allocated reasonably. For vehicles that are close to full charge, the allocated power is reduced appropriately to save resources for other vehicles that need it more.

[0029] Real-time updates and feedback control: Because vehicle status (such as SOC) changes over time, power distribution strategies need to be reassessed and adjusted periodically (e.g., every minute).

[0030] Considering future demand forecasts: To further enhance the system's flexibility and adaptability, historical data can be analyzed to predict charging demand trends over a future period. This allows for a margin in current power allocation, preventing disruption to existing allocation plans due to newly added high-demand vehicles.

[0031] Beneficial effects: Compared with existing technologies, this priority-based dynamic power allocation system and method for charging piles has the following advantages: Efficient use of power resources: Through dynamic power allocation, resource waste is avoided and the overall output efficiency of charging piles is improved.

[0032] Improve charging efficiency: Prioritize charging power for high-demand vehicles and shorten their charging time.

[0033] Flexible adaptation to various scenarios: The allocation strategy can be flexibly adjusted according to user level, reservation status, etc.

[0034] Enhance user experience: Reduce user waiting time and improve the intelligence level of the charging process.

[0035] It is scalable and compatible: it supports the charging needs of more car models and higher power levels in the future. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a system structure block diagram of the present invention; Figure 2 This is a flowchart of the multi-vehicle access scheduling process of the present invention. Detailed Implementation

[0038] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0039] Please see Figures 1-2 As shown, this invention provides a technical solution: a priority-based dynamic power allocation system for charging piles, characterized by comprising a vehicle information acquisition module, a charging pile status monitoring module, a priority evaluation module, a power allocation module, and a user interaction module. The vehicle information acquisition module is used to collect in real time the vehicle's current SOC value, target SOC value, vehicle power demand, vehicle type, user type, and payment mode.

[0040] The charging pile status monitoring module is used to monitor the number of modules, the number of modules used, and the number of modules remaining in the charging pile in real time.

[0041] Priority assessment module: Based on the data provided by the vehicle information collection module and the charging pile status monitoring module, assess the charging priority of each vehicle.

[0042] Power allocation module: Based on the evaluation results of the priority evaluation module, dynamically allocates charging pile modules to meet the charging needs of vehicles.

[0043] User interaction module: Used to display the current charging priority, estimated charging time and module allocation to the user, and to provide user guidance functions.

[0044] The vehicle information collection module can identify and adapt to different types of electric vehicles and their specific needs.

[0045] The priority assessment module uses a comprehensive scoring mechanism to calculate the priority score for each vehicle. This score is based on factors such as current SOC, required power, vehicle type, user type, and payment mode.

[0046] Vehicle types include different types of vehicles such as private cars, taxis, buses, and logistics vehicles.

[0047] The power distribution module can adjust the charging priority and module allocation of each vehicle in real time during the charging process to cope with resource changes.

[0048] The system also includes an exception handling mechanism that immediately releases module resources for subsequent vehicles in the queue if a vehicle prematurely pulls its gun.

[0049] A priority-based dynamic power allocation method for charging piles includes the following steps: 1) Real-time collection of information such as the vehicle's current SOC value, target SOC value, vehicle power demand, vehicle type, user type, and payment mode.

[0050] 2) Real-time monitoring of information such as the number of modules in the charging pile, the number of modules used, and the number of modules remaining.

[0051] 3) Calculate the required charging power for the vehicle based on its current SOC value and target SOC value. Combine this with the vehicle's power demand and the number of remaining modules in the charging station to assess the charging priority of each vehicle.

[0052] 4) Based on the priority assessment results, the modules of the charging pile are dynamically allocated. Vehicles with higher priority are allocated more modules, and vehicles with lower priority are allocated fewer modules, but vehicles with less demand will occupy at least one power module.

[0053] 5) During the charging process, monitor the vehicle's charging status and the changes in charging pile resources in real time, and dynamically adjust the vehicle's charging priority and module allocation.

[0054] Please refer to the following carefully. Figure 1 This block diagram illustrates a modular charging station system. Centered on a main control unit, it acquires vehicle information via a communication interface and intelligently allocates resources within the power module group using a scoring calculation and resource scheduling module. The system also includes a user interface, safety protection mechanisms, and external system interfaces to ensure an efficient and safe charging experience. The overall design supports flexible expansion and dynamic adjustment, improving the quality and efficiency of charging services.

[0055] Power demand ranking and priority determination Step 1: Introduce a comprehensive scoring mechanism: For each connected vehicle, a comprehensive score is calculated based on its current SOC, power demand vehicle type, user type, payment mode, etc.

[0056] The calculation formula is: Score_i = w1 × Preq_i + w2 × (1 - SOC_i) + w3 × Vehicle_i + w4 × User_i + w5 × Mode_i, where Preq_i is the power demand of the i-th vehicle, SOC_i is its current state of charge, Vehicle_i is its vehicle type (e.g., private car, taxi, bus, logistics vehicle), User_i is its user category (e.g., regular user, VIP user, reservation user), and Mode_i is its payment method (e.g., prepaid, postpaid, membership card payment). w1, w2, w3, w4, and w5 are the weighting coefficients for these parameters, which can be adjusted according to actual conditions. The purpose of using 1 - SOC_i is to give higher priority to vehicles with lower battery levels.

[0057] Step 2: Dynamically adjust the weights: The weights of each parameter can be dynamically adjusted based on different times of day or special events (such as holidays). For example, during off-peak hours, the value of w2 can be increased, thus favoring vehicles that are close to depleted but still need some time to charge; while during peak hours, the weight of w2 can be appropriately reduced to ensure that high-power-demand vehicles can obtain the required power as quickly as possible.

[0058] Power Allocation Algorithm Constraint-based linear programming models: The power allocation problem is solved by constructing a linear programming model. The objective function aims to maximize the sum of satisfaction scores for all vehicles, while adhering to the following constraints: Maximum output power limit for a single pile; Each vehicle is assigned at least one module; Maximum output power limit for each charging gun; The actual charging power of a vehicle must not exceed its required power. For each vehicle's SOC, power is allocated reasonably. For vehicles that are close to full charge, the allocated power is reduced appropriately to save resources for other vehicles that need it more.

[0059] Real-time updates and feedback control: Because vehicle status (such as SOC) changes over time, power distribution strategies need to be reassessed and adjusted periodically (e.g., every minute).

[0060] Considering future demand forecasts: To further enhance the system's flexibility and adaptability, historical data can be analyzed to predict charging demand trends over a future period. This allows for a margin in current power allocation, preventing disruption to existing allocation plans due to newly added high-demand vehicles.

[0061] Please refer to the following carefully. Figure 2 This is a flowchart illustrating the multi-vehicle access scheduling process. It describes how the system dynamically allocates power modules based on a scoring model when multiple vehicles access a charging station. The process begins with vehicle access, proceeding through steps such as information collection, initial allocation, scoring and sorting, resource reallocation, and finally, appropriate processing measures are taken upon completion of charging.

[0062] One embodiment of the present invention: This embodiment uses a 1000kW high-power split-type DC charging system as an example to illustrate an intelligent modular power scheduling method under conditions of multiple vehicles simultaneously connected and limited resources. The system consists of multiple 40kW power modules, supporting up to 25 modules operating in parallel, with a total output power of up to 1000kW. Each charging gun supports a maximum of 5 modules supplying power simultaneously, meaning a maximum single-gun output power of 200kW.

[0063] The system has a vehicle priority evaluation mechanism. Based on the current battery state (SOC) and power demand of each vehicle, the priority is calculated through a weighted scoring model, thereby realizing the dynamic allocation and scheduling of module resources.

[0064] System basic parameters:

[0065] Scoring formula: Score_i=w1×Preq_i+w2×(1-SOC_i)+w3×Vehicle_i+w4×User_i+w5×Mode_i Where w1=0.5, w2=0.4, w3=0, w4=0, w5=0 Scheduling objective: Each vehicle must receive at least one power module; All modules must be used and cannot be left idle. High-priority vehicles will be given priority in meeting their power requirements. When resources are scarce, priority is given to vehicles with high ratings, and vehicles with low ratings are allocated as much as possible using the remaining resources. The output of a single gun shall not exceed the hardware limit (200kW).

[0066] Allocation logic: Step 1: Basic Support Phase.

[0067] Objective: Ensure that each vehicle receives at least one module.

[0068] Operation: Assign 1 module to each vehicle, consuming a total of 10 modules.

[0069] Number of remaining modules: 25 - 10 = 15.

[0070] Step 2: The remaining modules are allocated according to the ranking of the scores.

[0071] Objective: Assign remaining modules to vehicles based on their scores, from highest to lowest, until the requirements are met or no modules remain.

[0072] Final allocation results:

[0073] Effects and advantages: Fairness guarantee: All vehicles have received at least one module, reflecting the principle of fairness in the system.

[0074] Dynamic scheduling capability: Based on scoring and ranking, the system prioritizes the needs of high-priority vehicles under limited resource conditions, thus achieving intelligent scheduling.

[0075] Maximizing resource utilization: All 25 modules were used efficiently, avoiding waste.

[0076] Extended Implementation Example: Dynamic weight update mechanism: As the charging process progresses, vehicle scores are recalculated and priorities are adjusted to improve fairness.

[0077] Predictive model-assisted decision-making: Machine learning is used to predict the power demand of vehicles in subsequent stages and reserve resources in advance.

[0078] Anomaly handling mechanism: If a vehicle pulls out its gun prematurely, the module resources are released to subsequent vehicles in the queue.

[0079] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0080] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A priority-based dynamic power allocation system for charging piles, characterized in that: It includes a vehicle information collection module, a charging pile status monitoring module, a priority evaluation module, a power allocation module, and a user interaction module. The vehicle information collection module is used to collect the vehicle's current SOC value, target SOC value, vehicle power demand, vehicle type, user type, and payment mode in real time. The charging pile status monitoring module is used to monitor the number of modules, the number of modules used, and the number of modules remaining in the charging pile in real time. Priority assessment module: Based on the data provided by the vehicle information collection module and the charging pile status monitoring module, assess the charging priority of each vehicle; Power allocation module: Based on the evaluation results of the priority evaluation module, dynamically allocates the charging pile module to meet the charging needs of the vehicle. User interaction module: Used to display the current charging priority, estimated charging time and module allocation to the user, and to provide user guidance functions.

2. The priority-based dynamic power allocation system and method for charging piles according to claim 1, characterized in that: The vehicle information collection module can identify and adapt to different types of electric vehicles and their specific needs.

3. The priority-based dynamic power allocation system and method for charging piles according to claim 1, characterized in that: The priority evaluation module uses a comprehensive scoring mechanism to calculate the priority score for each vehicle. This score is based on factors such as current SOC, required power, vehicle type, user type, and payment mode.

4. The priority-based dynamic power allocation system and method for charging piles according to claim 1, characterized in that: The vehicle types include different types of vehicles such as private cars, taxis, buses, and logistics vehicles.

5. The priority-based dynamic power allocation system and method for charging piles according to claim 1, characterized in that: The power allocation module can adjust the charging priority and module allocation of each vehicle in real time during the charging process to cope with resource changes.

6. The priority-based dynamic power allocation system and method for charging piles according to claim 1, characterized in that: The system also includes an exception handling mechanism that immediately releases module resources for use by subsequent vehicles in the queue when a vehicle prematurely pulls out its gun.

7. A priority-based dynamic power allocation method for charging piles, characterized in that: Includes the following steps: 1) Real-time collection of information such as the vehicle's current SOC value, target SOC value, vehicle power demand, vehicle type, user type, and payment mode; 2) Real-time monitoring of information such as the number of modules in the charging pile, the number of modules used, and the number of modules remaining; 3) Calculate the required charging power for the vehicle based on its current SOC value and target SOC value, and assess the charging priority of each vehicle by combining the vehicle's power demand and the number of remaining modules in the charging station. 4) Based on the priority assessment results, the modules of the charging pile are dynamically allocated; vehicles with higher priority are allocated more modules, vehicles with lower priority are allocated fewer modules, but vehicles with less demand will occupy at least one power module. 5) During the charging process, monitor the vehicle's charging status and the changes in charging pile resources in real time, and dynamically adjust the vehicle's charging priority and module allocation.

8. The priority-based dynamic power allocation system and method for charging piles according to claim 1, characterized in that: In the priority evaluation step, the priority score of each vehicle is determined by calculating the formula Score_i=w1×Preq_i+w2×(1-SOC_i)+w3×Vehicle_i+w4×User_i+w5×Mode_i.

9. A priority-based dynamic power allocation system and method for charging piles according to claim 1, characterized in that: In the real-time adjustment step of step 5, the system will dynamically adjust the weight coefficients of each parameter according to different time periods of the day or special events.

10. A priority-based dynamic power allocation system and method for charging piles according to claim 1, characterized in that: In the power allocation step of step 4, a constraint-based linear programming model is used to maximize the sum of satisfaction scores of all vehicles while adhering to constraints such as the maximum output power limit of a single pile and the requirement that each vehicle be allocated at least one module.

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