Intelligent mobile energy storage charging platform system based on building photovoltaic integration

Abstract

The invention discloses an intelligent mobile energy storage charging platform system based on building photovoltaic integration, which comprises a BIPV photovoltaic power generation module, a mobile energy storage charging platform and an intelligent scheduling cloud platform, and is characterized in that the mobile energy storage charging platform is in network connection with the BIPV photovoltaic power generation module and the intelligent scheduling cloud platform; the mobile energy storage charging platform is carried on an unmanned vehicle, and the intelligent scheduling cloud platform receives state feedback of the mobile energy storage charging platform and position information and battery charge state data of each vehicle to form scheduling instruction information. And the mobile energy storage charging and replacing platform is instructed to drive to the corresponding charging and replacing vehicle for charging and replacing or to drive to the BIPV photovoltaic power generation module for energy supplementation. According to the invention, the green electricity generated by the BIPV photovoltaic power generation module is utilized to provide charging and battery replacement services for the new energy vehicle, the green electricity consumption rate is improved from 30% to 98% or more, and the charging convenience and the vehicle use experience are improved through a charging mode of finding a vehicle by a pile and a battery-to-battery mode of finding a vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of intersection between new energy applications and intelligent transportation technologies, and specifically to an intelligent mobile energy storage and charging platform system based on building photovoltaic integration. Background Art

[0002] Large-span buildings like logistics warehouses have high photovoltaic coverage rates (≥80%), but the traditional "self-generation for self-use" model is limited by fluctuating building electricity loads (daytime loads are only 30%-50% of photovoltaic power generation). This results in a large amount of green electricity being wasted, creating a bottleneck in green electricity consumption. Currently, most fixed charging stations rely on grid power, failing to effectively utilize distributed photovoltaic resources. This has exacerbated the load on urban distribution networks, with peak-to-valley fluctuations reaching 40% in some areas.

[0003] According to statistics, over 80% of new energy vehicle owners are unable to install private charging piles due to space constraints and must rely on public charging stations. In typical scenarios, the average waiting time for charging exceeds 40 minutes. Traditional fixed charging piles use a "car finds the pile" model, requiring users to go to the charging station specifically. The average single charge time (including round trip) exceeds 1.5 hours, significantly reducing the user experience.

[0004] Furthermore, existing mobile charging solutions rely heavily on manual scheduling, lacking autonomous coordination between charging platforms and vehicles. Furthermore, the battery storage module capacity (<50kWh) and charging rate (≤1C) are insufficient to meet the continuous recharging needs of multiple vehicles. In closed environments like mining areas and docks, unmanned vehicles offer a foundation for efficient battery swapping due to their uniform battery specifications. However, existing technologies lack a mobile battery swap system integrated with BIPV green electricity, preventing the effective utilization of surplus PV power. Summary of the Invention

[0005] In response to the above-mentioned problems and shortcomings, the present invention provides an intelligent mobile energy storage charging and swapping platform system based on building photovoltaic integration, which aims to solve the problems of uneven spatial layout of new energy vehicle charging facilities, low user charging efficiency and insufficient green electricity consumption rate. Through the deep coupling of "photovoltaic-energy storage-charging / battery swapping", it can achieve 100% on-site consumption of green electricity and "zero mileage anxiety" service for new energy vehicles.

[0006] The present invention adopts the following technical solutions: An intelligent mobile energy storage charging and swapping platform system based on building photovoltaic integration, the system includes a BIPV photovoltaic power generation module, a mobile energy storage charging and swapping platform and an intelligent scheduling cloud platform, the BIPV photovoltaic power generation module is deployed on the roof of the building, the mobile energy storage charging and swapping platform is respectively connected to the BIPV photovoltaic power generation module and the intelligent scheduling cloud platform network, the mobile energy storage charging and swapping platform is carried on an unmanned vehicle, the intelligent scheduling cloud platform receives status feedback of the mobile energy storage charging and swapping platform and the location information and battery charge status data of each vehicle, forms scheduling instruction information, and instructs the mobile energy storage charging and swapping platform to travel to the corresponding charging and swapping vehicle for charging or to travel to the BIPV photovoltaic power generation module for energy replenishment.

[0007] Preferably, the mobile energy storage and charging and swapping platform includes a battery energy storage module, a drive module and a mechanical grasping module. The battery energy storage module adopts 2C~3C fast charging. The drive module receives the scheduling instruction information of the intelligent scheduling cloud platform, and drives to the charging point through its own self-powered battery pack to charge the vehicle or drives to the BIPV photovoltaic power generation module for energy replenishment; the mechanical grasping module includes a six-axis charging robotic arm and a charging gun, and the charging gun matches the charging interface of the charging vehicle.

[0008] Furthermore, the mechanical grasping module also includes a seven-axis battery-swapping robotic arm, which is provided with a control module, an infrared recognition module, a 3D positioning module and a force control sensor integrated at the end of the seven-axis battery-swapping robotic arm. The seven-axis battery-swapping robotic arm cooperates with the standardized battery-swapping potential configured in the fixed-point battery-swapping area to perform battery-swapping. The infrared recognition module and the 3D positioning module locate the battery-swapping area of the battery-swapping vehicle. The control module controls the seven-axis battery-swapping robotic arm to grasp the battery-swapping battery, and controls the battery-swapping docking pressure through the force control sensor.

[0009] Furthermore, the six-axis charging robotic arm is provided with a control module, an infrared recognition module, a 3D positioning module and a force control sensor integrated at the end of the six-axis charging robotic arm. The infrared recognition module and the 3D positioning module are used to locate the vehicle charging interface. The control module controls the charging gun to move to the vehicle charging interface and controls the charging docking pressure through the force control sensor.

[0010] Preferably, the battery energy storage module in the mobile energy storage charging and swapping platform is equipped with a 200kWh lithium iron phosphate battery pack and is configured with a liquid cooling management module to control the battery temperature difference to ≤3°C, the cycle life of the rechargeable battery to ≥6000 times, and the cycle life of the swapping battery with a discharge depth of 70% to ≥3000 times.

[0011] Preferably, the intelligent scheduling cloud platform adopts a three-level collaborative control model of "photovoltaic-energy storage-vehicle" based on the 5G-V2X communication protocol, which includes a photovoltaic prediction layer, a task allocation layer and a user interaction layer. The photovoltaic prediction layer accesses meteorological satellite data to predict the power generation of the BIPV photovoltaic power generation module in the next 24 hours; the task allocation layer uses an improved ant colony algorithm to dynamically optimize the moving path of the mobile energy storage charging and swapping platform; the user interaction layer uses an application to execute charging demand submission, fee settlement and charging progress visualization.

[0012] Furthermore, the task allocation layer in the intelligent scheduling cloud platform communicates data with the vehicle operation platform. The intelligent scheduling cloud platform uses the API interface to obtain the real-time positioning data and charge status data of each vehicle in the vehicle operation platform, and inputs the battery swap demand prediction model. The high-demand battery swap area within the future set time period is calculated based on the designated electronic fence, and the dynamic battery swap priority calculation is performed for the vehicles in the high-demand battery swap area to obtain the priority battery swap vehicles and transmit them to the mobile energy storage charging and swapping platform.

[0013] Preferably, the algorithm for obtaining high-demand battery swapping areas in the battery swapping demand prediction model is: ; Among them: α, β, γ are weight values, α+β+γ=1; SOC(t-1) is the remaining capacity of the electric vehicle battery at time t-1; Density(t-1) is the vehicle density in the battery swapping area at time t-1; Historical(t) is the historical battery replacement data or historical load data.

[0014] Preferably, the battery swap demand prediction model performs dynamic battery swap priority calculation for high-demand battery swap areas, and the algorithm is: ; Among them: Urgency_i is the vehicle urgency set by the vehicle operation platform; Distance_i is the current distance between the vehicle and the mobile energy storage charging and swapping platform; SOC_i is the current state of charge of the vehicle.

[0015] Furthermore, the mobile energy storage charging and swapping platform is also provided with a battery health management module, which is used to detect the internal resistance and temperature of the battery energy storage module during battery swapping, and automatically return the battery energy storage module that exceeds the set threshold to the BIPV photovoltaic power generation module for slow charging repair.

[0016] Compared with the prior art, the present invention has the following advantages: A. The intelligent mobile energy storage charging and battery swapping platform system provided by the present invention adopts a closed-loop model of "photovoltaic power generation-mobile energy storage-dynamic charging and battery swapping". It uses an intelligent scheduling cloud platform to obtain vehicles that need charging and battery swapping. Then, unmanned vehicles equipped with the mobile energy storage charging and battery swapping platform actively find vehicles to be charged and swapped. The average waiting time for charging users is shortened to less than 15 minutes, and battery swapping users (shared electric vehicles) do not need to stop and wait. This can save car owners / operators approximately 80 hours (charging) + 300 hours (battery swapping) in time costs each year, and improve user experience. The present invention uses the green electricity generated by BIPV photovoltaic power generation modules to provide charging and battery swapping services for new energy vehicles, and the green electricity consumption rate is increased from 30% to more than 98%. Through the mobile energy storage charging and battery swapping platform, a "pile finds car" charging mode and a "battery finds car" battery swapping mode are realized, improving charging convenience and energy utilization efficiency, and enhancing the driving experience of electric vehicles. In particular, it solves the problem of efficient energy replenishment for unmanned vehicles and two-wheeled shared electric vehicles in closed scenarios.

[0017] B. The present invention collects the real-time positioning data, charge status data, status feedback data of the mobile energy storage charging and swapping platform of each vehicle through the intelligent scheduling cloud platform, and calculates the power generation of the BIPV photovoltaic power generation module, calculates the dynamic battery swapping priority of each vehicle in the future period, and performs preferential battery swapping for vehicles that are in urgent need of electricity, which greatly improves the battery swapping efficiency and reduces waiting time.

[0018] C. The mechanical grasping module set up on the mobile energy storage charging and swapping platform of the present invention includes a six-axis charging robot arm and a seven-axis battery swapping robot arm, and a force control sensor is set at the end of each robot arm. The infrared recognition module and the 3D positioning module are used to achieve millimeter-level docking between the charging gun and the vehicle interface. The force control sensor is used to control the charging and swapping docking pressure to avoid damage to the vehicle interface.

[0019] D. The present invention utilizes a mobile energy storage charging and swapping platform to enable alternate charging of multiple vehicles on the same platform, improving overall service efficiency by 40%. In the battery swapping mode, a single charging and swapping platform can serve 22 two-wheeled vehicles per day, and the battery is protected by a liquid cooling management module to avoid the impact of deep charging and discharging on battery life.

[0020] E. The present invention can achieve 100% absorption of the power generated by distributed photovoltaic power stations through intelligent scheduling, using the mobile energy storage charging and swapping platform as an intelligent energy storage device, and maximize self-generation and self-use without impacting the main power grid. At the same time, the mobile energy storage charging and swapping platform can achieve two-way charging and two-way discharging through the background intelligent management platform and with the help of 5G and AI technology, thereby maximizing profits. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the specific embodiments of the present invention, the following will briefly introduce the drawings required for use in the specific embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0022] Figure 1 This is a schematic diagram of the intelligent mobile energy storage and charging platform system provided by the present invention; Figure 2 This is a diagram of the composition of the intelligent scheduling cloud platform provided by the present invention; Figure 3 This is a diagram showing the composition of the mobile energy storage and charging / swapping platform provided by the present invention; Figure 4 This is a flow chart for battery replacement for shared electric vehicles provided by the present invention; Figure 5 This is a simplified structural diagram of the six-axis charging robotic arm provided by the present invention.

[0023] The meanings of the symbols in the figure are as follows: 1-vehicle base; 2-fixed legs; 3-joints; 4-movable legs; 5-control module 6-Torso; 7-Movable arm; 8-Gun line storage compartment; 9-3D positioning module 10-Infrared recognition module and force control sensor; 20-Charging gun. DETAILED DESCRIPTION

[0024] The technical solution of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0025] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer," etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings and are intended solely to facilitate and simplify the description of the present invention. They are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation, and therefore should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0026] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0027] like Figure 1 As shown, the present invention provides an intelligent mobile energy storage charging and swapping platform system based on building photovoltaic integration, including a BIPV photovoltaic power generation module, a mobile energy storage charging and swapping platform and an intelligent scheduling cloud platform. The BIPV photovoltaic power generation module is deployed on the roof of the building, and the mobile energy storage charging and swapping platform is connected to the BIPV photovoltaic power generation module and the intelligent scheduling cloud platform network respectively. The mobile energy storage charging and swapping platform is mounted on an unmanned vehicle with a built-in navigation map. The intelligent scheduling cloud platform receives status feedback from the mobile energy storage charging and swapping platform and the location information and battery charge status data of each vehicle to form scheduling instruction information, and instructs the mobile energy storage charging and swapping platform to drive to the corresponding charging and swapping vehicle for charging and swapping or to drive to the BIPV photovoltaic power generation module for energy replenishment. For example, the BIPV photovoltaic power generation module deploys a 1MW-class BIPV system on the roof of a building such as a logistics warehouse, preferably using monocrystalline silicon BC components, combined with double-sided power generation and intelligent tracking technology, with a theoretical daily power generation of 6000kWh and a photovoltaic conversion efficiency of ≥24%. The appropriate photovoltaic power generation module is configured according to the building area of the logistics warehouse and the number of charging and swapping vehicles. This is not limited to the 1MW-class BIPV system provided.

[0028] The BIPV photovoltaic power generation modules include: HPBC double-glass step-on modules, string inverters and intelligent well network cabinets. The HPBC double-glass step-on modules adopt double-glass frameless and intelligent control, with a conversion efficiency of 23.9%. The string inverter adopts module-level MPPT control, with a power generation efficiency of ≥99.5%. The intelligent well network cabinet adopts data collection and automatic isolation of transmission faults.

[0029] like Figure 3As shown, the mobile energy storage charging and swapping platform includes a battery energy storage module, a drive module, and a mechanical grasping module. The battery energy storage module adopts 2C~3C fast charging. The drive module receives the dispatch instruction information of the intelligent dispatching cloud platform and drives to the charging point through its own self-powered battery pack to charge the vehicle or drives to the BIPV photovoltaic power generation module for energy replenishment; the mechanical grasping module includes a six-axis charging robot arm and a charging gun, and the charging gun matches the charging interface of the charging vehicle. The present invention carries the mobile energy storage charging and swapping platform on an unmanned vehicle. The unmanned vehicle receives the charging and swapping instruction information sent by the intelligent dispatching cloud platform. The unmanned vehicle will automatically drive to the target vehicle. After arriving at the target vehicle, the charging gun is used to realize the charging and swapping function of the target vehicle.

[0030] This invention uses unmanned vehicles equipped with a mobile energy storage charging and swapping platform to proactively seek out other vehicles for charging and swapping, significantly improving the user experience. The average waiting time for charging users is reduced to under 15 minutes, and swapping users (shared electric vehicles) no longer need to stop and wait. This proactive vehicle-seeking and swapping service saves vehicle owners and operators approximately 80 hours (charging) and 300 hours (swapping) in time costs annually. Because the vehicles are powered by green electricity generated by photovoltaic power generation, the closed-loop "photovoltaic power generation - mobile energy storage - dynamic charging and swapping" system increases the green electricity consumption rate from 30% to over 98%, significantly improving green electricity consumption.

[0031] The unmanned vehicle preferably used in the present invention adopts a lightweight aluminum alloy frame as its body, with a total mass of ≤1.5 tons (charging mode) / 2.0 tons (battery replacement mode), meeting the height limit requirements of urban roads (≤2.5m).

[0032] The battery energy storage module in the mobile energy storage charging and swapping platform is preferably equipped with a 200kWh lithium iron phosphate battery pack (of course not limited to) that supports 2C-3C fast charging, with a maximum power of 400kW, and a single full charge can serve 3-4 new energy vehicles; and is equipped with a liquid cooling management module to control the battery temperature difference to ≤3°C, the cycle life of the rechargeable battery to ≥6000 times, and the cycle life of the swapping battery with a discharge depth of 70% to ≥3000 times.

[0033] The driving module on the unmanned vehicle adopts self-powered driving technology equipped with a battery pack, with a cruising range of ≥150km, and supports autonomous round-trip energy replenishment between photovoltaic charging stations and charging points.

[0034] As a further preferred embodiment of the present invention, charging can be achieved by automatically docking the vehicle charging interface, such as Figure 5As shown, the six-axis charging manipulator comprises a vehicle-mounted base 1, fixed legs 2 fixed to the vehicle-mounted base 1, movable legs 4, a trunk 6, movable arms 7, a gun cable storage compartment 8, a 3D positioning module 9, and a charging gun 20. Joints are provided between the fixed legs 2 and the movable legs 4, joints 3 are provided between the trunk and the movable legs and arms, joints 3 are provided between the two movable arms 7, joints 3 are provided between the movable arms 7 and the gun cable storage compartment 8, and joints 3 are provided between the gun cable storage compartment 8 and the 3D positioning module 9. A total of six joints 3 make the six-axis charging manipulator more flexible. The vehicle-mounted base 1 is mounted on the unmanned vehicle. The control module is mounted on the trunk 6. The infrared recognition module and force control sensor 10 are integrated with the charging gun 20 and the 3D positioning module, respectively. The infrared recognition module and the 3D positioning module are used to locate the vehicle's charging interface. The control module 5 controls the displacement of the charging gun 20 to the vehicle's charging interface and uses a force control sensor to control the charging docking pressure, which is ≤50N to avoid damage to the vehicle interface. The infrared recognition module used preferably adopts infrared thermal imaging method, and the 3D positioning module preferably adopts 3D visual positioning with an error of ≤1mm, so as to realize automatic millimeter-level docking between the charging gun and the vehicle interface.

[0035] The six-axis charging robot arm is modeled using Denavit-Hartenberg parameterization, and the positioning error δ of its end effector positioning vehicle interface is 总 formula: ; Among them: Among them: δ 总 : represents the total positioning error of the six-axis charging robot arm end effector positioning vehicle interface, reflecting the comprehensive measurement of the position deviation of the robot arm during the positioning process; i: is the index variable for summation, ranging from 1 to 6, corresponding to the six joints of the six-axis charging robot arm, used to traverse and calculate the contribution of each joint to the total error; f: It is generally a function that describes the relationship between the position of the end effector of the robot arm (or the posture related to positioning, etc.) and the joint variables. That is, it is a mapping function of the end effector posture to the joint variables obtained through Denavit-Hartenberg parametric modeling. It reflects how the change of joint variables affects the position of the end effector and other positioning-related quantities; θ i : The joint variable of the i-th joint (such as the joint angle, which depends on the type of robot joint and the modeling method) is one of the key parameters that determine the position of the end effector of the robot arm; △θ i : The change in the i-th joint variable, △θ i<0.01°, which reflects the fluctuation or error of the joint variables in actual operation. This fluctuation will be transmitted to the end effector through the kinematic relationship of the robot arm, thus causing positioning error; :Function f on the i-th joint variable θ i The partial derivative of the joint variable θ represents the sensitivity of the end effector position (described by f) to the change in the unit change of the i-th joint variable. i The larger the partial derivative of the "transfer coefficient" that affects the positioning of the end effector, the more significant the impact of the change in the joint variable on the end positioning.

[0036] This invention adopts a green electricity time-space shifting mechanism. During the photovoltaic power generation peak period from 9:00 to 15:00, the mobile energy storage charging and swapping platform uses the "peak-valley electricity price difference" as a constraint condition to prioritize storing green electricity in the battery energy storage module; during non-photovoltaic power generation periods (such as at night), the "photovoltaic surplus power + valley electricity" hybrid power supply mode is used to reduce the cost per kilowatt-hour.

[0037] At the same time, the mobile energy storage charging and swapping platform also supports dual-charging and dual-discharging energy management. The daily cycle number of a single platform is ≥ 2 times, and the SOC (state of charge) threshold of the energy storage unit is set at 20% to 90% to avoid the impact of deep charging and discharging on battery life.

[0038] The mobile energy storage charging and swapping platform also has a multi-vehicle collaborative charging protocol, which supports "alternate charging" of multiple vehicles on the same platform. For example, when vehicle A is charging, the platform will synchronously move to the position of vehicle B and complete docking preparations, improving overall service efficiency by 40%.

[0039] For vehicle battery swapping, the mechanical grasping module in the present invention also includes a seven-axis battery swapping robot arm for battery swapping. The seven-axis battery swapping robot arm is equipped with a control module, an infrared recognition module, a 3D positioning module, and a force control sensor integrated at the end of the seven-axis battery swapping robot arm. The seven-axis battery swapping robot arm cooperates with the standardized battery swapping potential configured in the fixed-point battery swapping area to swap batteries. The infrared recognition module and the 3D positioning module locate the battery swapping area of the battery swapping vehicle. The control module controls the seven-axis battery swapping robot arm to grab the battery swapping battery and controls the battery swapping docking pressure through the force control sensor to avoid damaging the vehicle. Of course, the present invention performs visual-force control joint calibration after every 500 battery swaps to ensure docking accuracy. In the battery swapping mode, a single platform serves 22 two-wheeled vehicles per day.

[0040] like Figure 2As shown, the intelligent scheduling cloud platform in the system of the present invention adopts a three-level collaborative control model of "photovoltaic-energy storage-vehicle" based on the 5G-V2X communication protocol, which includes a photovoltaic prediction layer, a task allocation layer and a user interaction layer. The photovoltaic prediction layer accesses meteorological satellite data to predict the power generation of BIPV photovoltaic power generation modules in the next 24 hours or 48 hours, achieving ultra-short-term prediction with an error of less than 5%. It can combine weather data for the next 24 or 48 hours to provide accurate analysis of short-term power generation, such as whether there will be rainy weather during the power generation period from 9 to 15 o'clock, thereby accurately estimating power generation and making advance judgments on the number and maximum range of mobile energy storage charging and swapping platforms available for scheduling. The task allocation layer uses an improved ant colony algorithm to dynamically optimize the moving path of the mobile energy storage charging and swapping platform. The improved ant colony algorithm used is as follows: ; Where: P k ij ( t )‌: represents the probability that ant k moves from node i to node j at time t, which is used to describe the possibility of an ant moving from one node to another when choosing a path; T ij (t): The pheromone concentration on the path between nodes i and j at time t. Pheromones are an important basis for guiding ants to choose paths in the ant colony algorithm. Ants tend to choose paths with high pheromone concentrations. The pheromone update mechanism (generally including volatilization and addition) will dynamically adjust the path later. η ij ( t ): The heuristic factor of node i at time t is usually related to the "goodness" of the path. For example, it can be the inverse of the distance from the node to node i (the closer the distance, the larger the heuristic factor, and the more ants tend to choose it). It is used to inspire ants to choose a better path, reflecting the guidance of the heuristic information of the problem itself on path selection; α: The influencing factor of pheromone concentration, which is used to control the weight of pheromone concentration in the calculation of path selection probability. The larger α is, the more ants tend to choose paths based on pheromone concentration. The preferred value is α = 2. β: The influencing factor of the heuristic factor, which is used to control the weight of the heuristic factor in the calculation of path selection probability. The larger β is, the more the ants rely on heuristic information (such as distance and other heuristic factors) when choosing a path. The preferred value is β = 5; Allowed k : The next node set that ant k can currently select is the set of nodes that the ant has not visited when it is at node i and can transfer to, which limits the range of nodes that the ant can transfer to next; Tis (t), η is (t): Meaning similar to T ij (t), η ij (t), but here is the node i to the set Allowed k The pheromone concentration and heuristic factor of the middle node s are used to participate in the summation of the denominator to normalize the probability and ensure ：P k ij ( t )‌ is a reasonable probability value (the sum of the probabilities of all possible transitions is 1); When α=2 and β=5, the simulation results show that the path planning efficiency can be improved by 37%.

[0041] The user interaction layer uses an application APP to submit charging requirements, settle fees and visualize charging progress. The APP integrates charging reservations, electronic fences and emergency braking functions, and the shared electric vehicle scenario supports automatic dispatching of battery replacements.

[0042] The present invention preferably interconnects the task allocation layer in the intelligent scheduling cloud platform with the vehicle operation platform data. The intelligent scheduling cloud platform uses the API interface to obtain the real-time positioning data (GPS error ≤ 10m) and charge status data (SOC threshold ≤ 20% triggers a battery replacement request) of each vehicle in the vehicle operation platform, and inputs the battery replacement demand prediction model. According to the designated electronic fence, the high-demand battery replacement area in the future set time period (for example, within the next 1 hour) is calculated, and the corresponding scheduling time is ≤ 2 minutes; dynamic battery replacement priority calculation is performed for vehicles in the high-demand battery replacement area, and priority battery replacement vehicles are obtained, and transmitted to the mobile energy storage charging and replacement platform.

[0043] The algorithm for obtaining high-demand battery swapping areas in the battery swapping demand prediction model is: ; Among them: α, β, γ are weight values, α+β+γ=1; SOC(t-1) is the remaining power of the electric vehicle battery at time t-1. The lower the remaining power, the higher the demand for battery replacement. Therefore, it is an important factor affecting the demand for battery replacement. Density(t-1) is the vehicle density in the area at time t-1. The higher the vehicle density, the more potential users with battery swapping needs and the higher the demand for battery swapping. Historical(t) is the historical battery swap data or historical load data. By analyzing the past battery swap demand in the area, including the frequency and amount of battery swaps in different time periods, we can explore the temporal patterns and trends of battery swap demand.

[0044] The dynamic battery swap priority calculation algorithm for high-demand battery swap areas in the battery swap demand forecasting model is: ; Urgency_i is the vehicle urgency set by the vehicle operation platform. It is 1 for shared electric vehicles and 0.8 for mining vehicles. Distance_i is the current distance between the vehicle and the mobile energy storage charging and swapping platform; SOC_i is the current state of charge of the vehicle.

[0045] The following two battery replacement scenarios are implemented separately: (1) Shared electric vehicle battery replacement Interoperate with the operation platform data, obtain vehicle location, power level, and riding trajectory through the API interface, and set the battery replacement response time within the electronic fence (radius 500m) to ≤10 minutes.

[0046] Unified two-wheeled vehicle battery dimensions (300mm×200mm×150mm) and interface specifications (GB / T 36945-2018), standardized batteries, and support plug-and-play.

[0047] (2) Unmanned battery replacement in mining areas Demarcate battery swapping areas, set up standardized battery swapping points along the main roads in the mining area, and equip them with positioning signs. The mobile energy storage charging and swapping platform uses UWB positioning to achieve centimeter-level docking. UWB (ultra-wideband) positioning is a high-precision positioning method based on ultra-wideband wireless communication technology, suitable for precise ranging and positioning.

[0048] In addition, the mobile energy storage charging and swapping platform is also equipped with a battery health management module, which is used to detect the internal resistance and temperature of the battery energy storage module each time the battery is swapped, and automatically return the battery energy storage module that exceeds the set threshold to the BIPV photovoltaic power generation module for slow charging repair.

[0049] Taking a cluster consisting of 10 mobile energy storage charging and swapping platforms as an example, the annual service capacity for new energy vehicles can reach 150,000 times (including 50,000 times of battery swapping), corresponding to a carbon emission reduction of approximately 15,000 tons. The operating cost is 42% lower than that of traditional charging stations, and the average daily revenue per vehicle of shared electric vehicle operators has increased by 83%.

[0050] The comparison between the system of the present invention and the traditional charging station is shown in the following table:

[0051] The following takes the battery replacement of a shared electric vehicle as an example to explain the battery replacement process in detail.

[0052] like Figure 4As shown in the figure, when the SOC of an electric vehicle is ≤20%, the electric vehicle power will generate a warning information. At this time, the vehicle operation platform will receive the warning information and upload the location and power data of the electric vehicle to the intelligent scheduling cloud platform. It will use the LSTM algorithm to predict demand, with a prediction response of 2 minutes, and optimize the path. At the same time, the intelligent scheduling cloud platform will send a scheduling instruction to the mobile energy storage charging and swapping platform (i.e., the mobile platform). The mobile platform will respond and go to the target location of the electric vehicle. After arriving at the battery swapping area where the electric vehicle is located, it will use its own seven-axis battery swapping robotic arm to perform the battery swapping. The battery swapping time is ≤3 minutes. At the same time, the battery swapping data will be transmitted back to the vehicle operation platform and the intelligent scheduling cloud platform, and the battery swapping is completed.

[0053] Any matters not described in the present invention are applicable to the prior art.

[0054] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will readily appreciate that other variations or modifications based on the above descriptions are possible. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. An intelligent mobile energy storage and charging platform system based on building photovoltaic integration, characterized in that: The system includes a BIPV photovoltaic power generation module, a mobile energy storage charging and swapping platform, and an intelligent scheduling cloud platform. The BIPV photovoltaic power generation module is deployed on the roof of the building. The mobile energy storage charging and swapping platform is connected to the BIPV photovoltaic power generation module and the intelligent scheduling cloud platform network respectively. The mobile energy storage charging and swapping platform is mounted on an unmanned vehicle. The intelligent scheduling cloud platform receives status feedback from the mobile energy storage charging and swapping platform and the location information and battery charge status data of each vehicle to form scheduling instruction information, and instructs the mobile energy storage charging and swapping platform to travel to the corresponding charging and swapping vehicle for charging or to travel to the BIPV photovoltaic power generation module for energy replenishment.

2. The intelligent mobile energy storage and charging and swapping platform system based on building photovoltaic integration according to claim 1 is characterized in that: The mobile energy storage and charging and swapping platform includes a battery energy storage module, a drive module and a mechanical grasping module. The battery energy storage module adopts 2C~3C fast charging. The drive module receives the scheduling instruction information of the intelligent scheduling cloud platform, and drives to the charging point through its own self-powered battery pack to charge the vehicle or drives to the BIPV photovoltaic power generation module for energy replenishment; the mechanical grasping module includes a six-axis charging robotic arm and a charging gun, and the charging gun matches the charging interface of the charging vehicle.

3. The intelligent mobile energy storage and charging and swapping platform system based on building photovoltaic integration according to claim 2 is characterized in that: The mechanical grasping module also includes a seven-axis battery-swapping robotic arm, which is equipped with a control module, an infrared recognition module, a 3D positioning module and a force control sensor integrated at the end of the seven-axis battery-swapping robotic arm. The seven-axis battery-swapping robotic arm cooperates with the standardized battery-swapping potential configured in the fixed-point battery-swapping area to perform battery-swapping. The infrared recognition module and the 3D positioning module locate the battery-swapping area of the battery-swapping vehicle. The control module controls the seven-axis battery-swapping robotic arm to grasp the battery-swapping battery, and controls the battery-swapping docking pressure through the force control sensor.

4. The intelligent mobile energy storage and charging and swapping platform system based on building photovoltaic integration according to claim 2 is characterized in that: The six-axis charging robotic arm is equipped with a control module, an infrared recognition module, a 3D positioning module and a force control sensor integrated at the end of the six-axis charging robotic arm. The infrared recognition module and the 3D positioning module are used to locate the vehicle charging interface. The control module controls the charging gun to move to the vehicle charging interface and controls the charging docking pressure through the force control sensor.

5. The intelligent mobile energy storage and charging platform system based on building photovoltaic integration according to any one of claims 1 to 4, characterized in that: The battery energy storage module in the mobile energy storage charging and swapping platform is equipped with a 200kWh lithium iron phosphate battery pack and a liquid cooling management module to control the battery temperature difference to ≤3°C. The cycle life of the rechargeable battery is ≥6000 times, and the cycle life of the swapping battery with a discharge depth of 70% is ≥3000 times.

6. The intelligent mobile energy storage and charging platform system based on building photovoltaic integration according to claim 5 is characterized in that: The intelligent scheduling cloud platform uses a three-level collaborative control model of "photovoltaic-energy storage-vehicle" based on the 5G-V2X communication protocol, which includes a photovoltaic prediction layer, a task allocation layer and a user interaction layer. The photovoltaic prediction layer accesses meteorological satellite data to predict the power generation of the BIPV photovoltaic power generation module in the next 24 hours; the task allocation layer uses an improved ant colony algorithm to dynamically optimize the movement path of the mobile energy storage charging and swapping platform; the user interaction layer uses an application to execute charging demand submission, fee settlement and charging progress visualization.

7. The intelligent mobile energy storage and charging and swapping platform system based on building photovoltaic integration according to claim 6 is characterized in that: The task allocation layer in the intelligent scheduling cloud platform communicates data with the vehicle operation platform. The intelligent scheduling cloud platform uses the API interface to obtain the real-time positioning data and charge status data of each vehicle in the vehicle operation platform, and inputs the battery replacement demand prediction model. According to the designated electronic fence, the high-demand battery replacement area within the future set time period is calculated, and the dynamic battery replacement priority calculation is performed for the vehicles in the high-demand battery replacement area to obtain the priority battery replacement vehicles and transmit them to the mobile energy storage charging and replacement platform.

8. The intelligent mobile energy storage and charging platform system based on building photovoltaic integration according to claim 7 is characterized in that: The algorithm for obtaining high-demand battery swapping areas in the battery swapping demand prediction model is: ； Among them: α, β, γ are weight values, α+β+γ=1; SOC(t-1) is the remaining capacity of the electric vehicle battery at time t-1; Density(t-1) is the vehicle density in the battery swapping area at time t-1; Historical(t) is the historical battery replacement data or historical load data.

9. The intelligent mobile energy storage and charging and swapping platform system based on building photovoltaic integration according to claim 7 is characterized in that: The algorithm for dynamic battery swap priority calculation for high-demand battery swap areas in the battery swap demand prediction model is: ； Among them: Urgency_i is the vehicle urgency set by the vehicle operation platform; Distance_i is the current distance between the vehicle and the mobile energy storage charging and swapping platform; SOC_i is the current state of charge of the vehicle.

10. The intelligent mobile energy storage and charging platform system based on building photovoltaic integration according to claim 1 is characterized in that: The mobile energy storage charging and swapping platform is also equipped with a battery health management module, which is used to detect the internal resistance and temperature of the battery energy storage module during battery swapping, and automatically return the battery energy storage module that exceeds the set threshold to the BIPV photovoltaic power generation module for slow charging repair.

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