An intelligent mobile energy storage, charging and swapping platform system based on building photovoltaic integration

Abstract

The application discloses a kind of intelligent mobile energy storage charging and swapping platform systems based on building photovoltaic integration, including BIPV photovoltaic power generation module, mobile energy storage charging and swapping platform and intelligent scheduling cloud platform, mobile energy storage charging and swapping platform is connected with BIPV photovoltaic power generation module, intelligent scheduling cloud platform network respectively, mobile energy storage charging and swapping platform is carried on unmanned vehicle, intelligent scheduling cloud platform receives the state feedback of mobile energy storage charging and swapping platform and the position information of each vehicle, battery state of charge data, forms scheduling instruction information, and instructs mobile energy storage charging and swapping platform to travel to corresponding charging and swapping vehicle to charge or travel to BIPV photovoltaic power generation module to supplement energy.The green electricity emitted by the BIPV photovoltaic power generation module is used to provide charging and swapping services for new energy vehicles, and the green electricity consumption rate is increased from 30% to more than 98%.Through the charging mode of pile finding car and the swapping mode of battery finding car, the charging convenience and driving experience are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of new energy application and intelligent transportation technology, and particularly relates to an intelligent mobile energy storage charging and battery swapping platform system based on building photovoltaic integration. BACKGROUND

[0002] Large-span buildings such as logistics warehouses have a high photovoltaic paving rate (≥80%), but the traditional "self-generation and self-use" mode is limited by the fluctuation of building power consumption (the daytime power consumption is only 30% to 50% of the photovoltaic power generation), resulting in a large amount of green electricity being abandoned, and there is a bottleneck in green electricity consumption. At present, most fixed charging piles rely on power grid power supply, and cannot effectively utilize distributed photovoltaic resources, which aggravates the load pressure of urban power distribution network, and the peak-valley difference in some areas reaches 40%.

[0003] According to statistics, more than 80% of new energy vehicle owners cannot install private charging piles due to site restrictions and need to rely on public charging stations. In typical scenarios, the average charging waiting time of users is more than 40 minutes. The traditional fixed charging pile adopts a "vehicle searching for pile" mode, and users need to specially go to the charging point. The average single charging time (including round trip) is more than 1.5 hours, which significantly reduces the user experience.

[0004] In addition, existing mobile charging solutions mostly rely on manual scheduling, and do not realize autonomous cooperation between the charging platform and the vehicle. The capacity (<50kWh) and charging rate (≤1C) of the battery energy storage module are difficult to meet the continuous energy supplement demand of multiple vehicles. In closed scenes such as mining areas and wharfs, unmanned vehicles have high-efficiency battery swapping basis due to the uniformity of battery specifications, but existing technologies lack mobile battery swapping systems combined with BIPV green electricity, resulting in that the excess photovoltaic electricity cannot be effectively utilized. SUMMARY

[0005] In view of the above problems and deficiencies, the present application provides an intelligent mobile energy storage charging and battery swapping platform system based on building photovoltaic integration, aiming to solve the problems of uneven spatial distribution 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", 100% local consumption of green electricity and "zero mileage anxiety" service for new energy vehicles are realized.

[0006] The present application adopts the following technical solutions:

[0007] The application discloses an intelligent mobile energy storage charging and replacing platform system based on building photovoltaic integration, which comprises a BIPV photovoltaic power generation module, a mobile energy storage charging and replacing platform and an intelligent scheduling cloud platform, wherein the BIPV photovoltaic power generation module is arranged on a building roof, the mobile energy storage charging and replacing platform is connected with the BIPV photovoltaic power generation module and the intelligent scheduling cloud platform in network, the mobile energy storage charging and replacing platform is mounted on an unmanned vehicle, and the intelligent scheduling cloud platform receives state feedback of the mobile energy storage charging and replacing platform, position information and battery state of charge data of each vehicle, forms scheduling instruction information, and instructs the mobile energy storage charging and replacing platform to drive to a corresponding charging and replacing vehicle for charging and replacing or to the BIPV photovoltaic power generation module for energy supplement.

[0008] Preferably, the mobile energy storage charging and replacing platform comprises a battery energy storage module, a driving module and a mechanical grabbing module, the battery energy storage module adopts 2C-3C fast charging, the driving module receives scheduling instruction information of the intelligent scheduling cloud platform, and drives to a charging point for charging a vehicle or to the BIPV photovoltaic power generation module for energy supplement through a self-mounted self-powered battery pack, the mechanical grabbing module comprises a six-axis charging mechanical arm and a charging gun, and the charging gun is matched with a charging interface of a charging vehicle.

[0009] Further, the mechanical grabbing module further comprises a seven-axis battery replacing mechanical arm, the seven-axis battery replacing mechanical arm is provided with a control module, an infrared identification module, a 3D positioning module and a force control sensor integrated at a tail end of the seven-axis battery replacing mechanical arm, the seven-axis battery replacing mechanical arm cooperates with a standardized battery replacing position arranged in a fixed-point battery replacing area for battery replacing, the infrared identification module and the 3D positioning module position a battery replacing area of a battery replacing vehicle, and the control module controls the seven-axis battery replacing mechanical arm to grab a battery for replacing and controls a replacing butt joint pressure through the force control sensor.

[0010] Further, the six-axis charging mechanical arm is provided with a control module, an infrared identification module, a 3D positioning module and a force control sensor integrated at a tail end of the six-axis charging mechanical arm, the infrared identification module and the 3D positioning module are used for positioning a vehicle charging interface, the control module controls the charging gun to shift to the vehicle charging interface, and a charging butt joint pressure is controlled through the force control sensor.

[0011] Preferably, the battery energy storage module in the mobile energy storage charging and replacing platform is mounted with a 200kWh lithium iron phosphate battery pack and is provided with a liquid cooling management module, a battery temperature difference is controlled to be less than or equal to 3 DEG C, a cycle life of a charging battery is greater than or equal to 6000 times, and a cycle life of a battery for replacing with a discharge depth of 70% is greater than or equal to 3000 times.

[0012] Preferably, the intelligent scheduling cloud platform adopts a "photovoltaic-energy storage-vehicle" three-level collaborative control model 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 module in the next 24 hours. The task allocation layer dynamically optimizes the mobile path of the mobile energy storage charging and swapping platform using an improved ant colony algorithm. The user interaction layer uses an application program to execute charging demand submission, fee settlement and charging progress visualization.

[0013] Further, the task allocation layer in the intelligent scheduling cloud platform interworks with the vehicle operation platform data. The intelligent scheduling cloud platform uses an API interface to obtain real-time positioning data and state of charge data of each vehicle in the vehicle operation platform, and inputs a battery swapping demand prediction model. According to the electronic fence drawn, the high-demand battery swapping area in the future set time period is calculated, the dynamic battery swapping priority of the vehicles in the high-demand battery swapping area is calculated, the priority battery swapping vehicles are obtained, and are transmitted to the mobile energy storage charging and swapping platform.

[0014] Preferably, the algorithm for obtaining the high-demand battery swapping area in the battery swapping demand prediction model is:

[0015] ;

[0016] Wherein: α, β, γ are weight values, α+β+γ=1;

[0017] SOC(t-1) is the residual capacity of the electric vehicle battery at t-1 time;

[0018] Density(t-1) is the vehicle density of the battery swapping area at t-1 time;

[0019] Historical(t) is historical battery swapping data or historical load data.

[0020] Preferably, the algorithm for dynamic battery swapping priority calculation in the high-demand battery swapping area in the battery swapping demand prediction model is:

[0021] ;

[0022] Wherein: Urgency_i is the vehicle urgency set by the vehicle operation platform;

[0023] Distance_i is the distance between the vehicle and the mobile energy storage charging and swapping platform;

[0024] SOC_i is the state of charge of the vehicle.

[0025] Further, the mobile energy storage charging and battery swapping platform is also provided with a battery health management module, which is used for detecting the internal resistance and temperature of the battery energy storage module during battery swapping, and automatically returning the battery energy storage module exceeding the set threshold to the BIPV photovoltaic power generation module for slow charging repair.

[0026] Compared with the prior art, the present application has the following advantages:

[0027] A. The intelligent mobile energy storage charging and battery swapping platform system provided by the present application adopts a "photovoltaic power generation-mobile energy storage-dynamic charging and battery swapping" closed loop mode, uses an intelligent scheduling cloud platform to obtain vehicles that need to be charged and swapped, and then actively finds the vehicles to be charged and swapped by the unmanned vehicle carrying the mobile energy storage charging and battery swapping platform. The average waiting time of charging users is shortened to 15 minutes, and the battery swapping users (shared electric vehicles) do not need to stop and wait, which can save about 80 hours (charging) + 300 hours (battery swapping) time cost for vehicle owners / operating companies per year, and the user experience is upgraded. The present application uses green electricity generated by the BIPV photovoltaic power generation module 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, the charging mode of "piles finding vehicles" and the battery swapping mode of "batteries finding vehicles" are realized, the charging convenience and energy utilization efficiency are improved, and the vehicle experience of electric vehicles is improved. In particular, the efficient energy supplement problem of unmanned vehicles and two-wheel shared electric vehicles in a closed scene is solved.

[0028] B. The present application collects real-time positioning data, state of charge data, state feedback data of the mobile energy storage charging and battery swapping platform of each vehicle through the intelligent scheduling cloud platform, and calculates the power generation of the BIPV photovoltaic power generation module. The dynamic battery swapping priority of each vehicle in a future period of time is calculated, the vehicles in urgent need of electricity are selected for battery swapping, the battery swapping efficiency is greatly improved, and the waiting time is reduced.

[0029] C. The present application sets a mechanical grabbing module on the mobile energy storage charging and battery swapping platform, which includes a six-axis charging mechanical arm and a seven-axis battery swapping mechanical arm, and sets a force control sensor at the end of each mechanical arm. By using an infrared identification module and a 3D positioning module, millimeter-level docking of the charging gun and the vehicle interface is realized. By using the force control sensor, the charging and battery swapping docking pressure is controlled to avoid damaging the vehicle interface.

[0030] D. The present application uses the mobile energy storage charging and battery swapping platform to realize the alternate charging of multiple vehicles on the same platform, and the overall service efficiency is improved by 40%. In the battery swapping mode, a single charging and battery swapping platform can serve 22 two-wheel vehicles per day, and the battery is protected by the liquid cooling management module to avoid the influence of deep charging and discharging on the battery life.

[0031] E.The application can realize 100% consumption of distributed photovoltaic power generation capacity through intelligent scheduling, and maximize self-generation and self-use, without impacting and influencing the main power grid. Meanwhile, the mobile energy storage charging and replacing platform can realize two charging and two discharging through the background intelligent management platform and 5G and AI technologies, and maximize the income. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the specific embodiments of the present application, the drawings needed in the specific embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0033] Figure 1 is the system principle diagram of the intelligent mobile energy storage charging and replacing platform provided by the present application;

[0034] Figure 2 is the composition diagram of the intelligent scheduling cloud platform provided by the present application;

[0035] Figure 3 is the composition diagram of the mobile energy storage charging and replacing platform provided by the present application;

[0036] Figure 4 is the flowchart for replacing batteries for shared electric vehicles provided by the present application;

[0037] Figure 5 is the structure diagram of the six-axis charging mechanical arm provided by the present application.

[0038] The meanings of the symbols in the figure are as follows:

[0039] 1-vehicle-mounted base; 2-fixed support leg; 3-joint; 4-movable support leg; 5-control module

[0040] 6-trunk; 7-movable support arm; 8-gun wire storage bin; 9-3D positioning module

[0041] 10-infrared identification module and force control sensor; 20-charging gun. DETAILED DESCRIPTION

[0042] The technical solutions of the present application will be described below in conjunction with the drawings. Obviously, the described embodiments are some embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0043] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and therefore cannot be understood as indicating or implying that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first", "second", "third" are only for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0044] In the description of the present application, it should be noted that unless otherwise explicitly specified and limited, the terms "mounting", "connection", "connection" should be understood broadly, for example, it can be fixed connection, or detachable connection, or integral connection; it can be mechanical connection, or electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or the internal communication of two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0045] As Figure 1 shown, the present application provides a kind of intelligent mobile energy storage charging and battery swapping platform system based on building photovoltaic integration, including BIPV photovoltaic power generation module, mobile energy storage charging and battery swapping platform and intelligent scheduling cloud platform, BIPV photovoltaic power generation module is deployed on building roof, mobile energy storage charging and battery swapping platform is connected with BIPV photovoltaic power generation module, intelligent scheduling cloud platform network respectively, mobile energy storage charging and battery swapping platform is carried on unmanned vehicle with built-in navigation map, intelligent scheduling cloud platform receives the state feedback of mobile energy storage charging and battery swapping platform and the position information of each vehicle, battery state of charge data, forms scheduling instruction information, and instructs mobile energy storage charging and battery swapping platform to drive to corresponding charging and battery swapping vehicle to charge or drive to BIPV photovoltaic power generation module to supplement energy.For example, BIPV photovoltaic power generation module is deployed 1MW level BIPV system on building roof such as logistics warehouse, preferably single-crystal silicon BC component is used, combined with double-sided power generation and intelligent tracking technology, theoretical daily power generation reaches 6000kWh, photovoltaic conversion efficiency is greater than or equal to 24%, according to the building area of logistics warehouse and the number of charging and battery swapping vehicles, configure the photovoltaic power generation module suitable for it, here is not limited to the 1MW level BIPV system provided.

[0046] The BIPV photovoltaic power generation module therein includes: HPBC double-glass treading component, string inverter and intelligent well network cabinet, the HPBC double-glass treading component therein adopts double-glass frameless and intelligent control, and the conversion efficiency is 23.9%, the string inverter adopts component-level MPPT control, and the power generation efficiency is greater than or equal to 99.5%, the intelligent well network cabinet adopts data acquisition and transmission fault automatic isolation.

[0047] As shown in Figure 3 The mobile energy storage charging and replacing platform comprises a battery energy storage module, a driving module and a mechanical grabbing module, the battery energy storage module adopts 2C-3C fast charging, the driving module receives the scheduling instruction information of the intelligent scheduling cloud platform, and drives to the charging point to charge the vehicle or drives to the BIPV photovoltaic power generation module to supplement energy through the self-powered battery pack carried by itself; the mechanical grabbing module comprises a six-axis charging mechanical arm and a charging gun, and the charging gun is matched with the charging interface of the charging vehicle. The mobile energy storage charging and replacing platform is carried on the unmanned vehicle, the unmanned vehicle receives the charging and replacing instruction information sent by the intelligent scheduling cloud platform, the unmanned vehicle automatically drives to the target vehicle, and after reaching the target vehicle, the charging gun is used to realize the charging and replacing function of the target vehicle.

[0048] The unmanned vehicle carrying the mobile energy storage charging and replacing platform actively searches for the vehicle for charging and replacing, greatly improves the user experience, shortens the average waiting time of the charging user to 15 minutes, and the replacing user (shared electric vehicle) does not need to stop and wait. Through the active vehicle searching and replacing service, the vehicle owner / operator can save about 80 hours (charging) + 300 hours (replacing) of time cost per year. Since the electric energy used by the vehicle is green electricity generated by photovoltaic power generation, through the "photovoltaic power generation-mobile energy storage-dynamic charging and replacing" closed loop, the green electricity consumption rate is increased from 30% to more than 98%, greatly improving the consumption rate of green electricity.

[0049] The vehicle body of the unmanned vehicle preferably adopted by the application adopts a lightweight aluminum alloy frame, the total mass is ≤1.5 tons (in charging mode) / 2.0 tons (in replacing mode), which meets the urban road height limit (≤2.5m) requirement.

[0050] The battery energy storage module in the mobile energy storage charging and replacing platform preferably carries a 200kWh lithium iron phosphate battery pack (of course not limited to) supporting 2C-3C fast charging, the maximum power is 400kW, and a single full charge can serve 3-4 new energy vehicles; and is configured with a liquid cooling management module to control the battery temperature difference ≤3℃, the cycle life of the charging battery ≥6000 times, and the cycle life of the replacing battery with a discharge depth of 70% ≥3000 times.

[0051] The driving module on the unmanned vehicle adopts a battery pack self-powered driving technology, the cruising range is ≥150km, and supports autonomous round-trip energy supplement between the photovoltaic charging station and the charging point.

[0052] As a further preferred embodiment of the application, the charging can realize automatic docking with the vehicle charging interface, such as Figure 5As shown, the six-axis charging robot arm adopted includes a vehicle base 1, a fixed leg 2 fixed on the vehicle base 1, a movable leg 4, a trunk 6, a movable arm 7, a gun wire storage bin 8, a 3D positioning module 9 and a charging gun 20. Joints are arranged between the fixed leg 2 and the movable leg 4, joints 3 are arranged between the trunk and the movable leg and the movable arm, joints 3 are arranged between the two movable arms 7, joints 3 are arranged between the movable arm 7 and the gun wire storage bin 8, and joints 3 are arranged between the gun wire storage bin 8 and the 3D positioning module 9, totaling six joints 3, making the entire six-axis charging robot arm more flexible. The vehicle base 1 is installed on an unmanned vehicle. The control module is installed on the trunk 6, the infrared recognition module and the 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 position the vehicle charging interface, the control module 5 controls the charging gun 20 to move to the vehicle charging interface, and the force control sensor controls the charging docking pressure, the docking pressure ≤ 50N, to avoid damaging the vehicle interface. The infrared recognition module preferably adopts an infrared thermal imaging method, and the 3D positioning module preferably adopts 3D visual positioning, with an error ≤ 1mm, to realize automatic millimeter-level docking of the charging gun and the vehicle interface.

[0053] The six-axis charging robot arm adopts Denavit-Hartenberg parameterization modeling, and the positioning error δ of the end effector of the six-axis charging robot arm in positioning the vehicle interface is 总 Formula:

[0054] ;

[0055] Wherein: wherein: δ 总 represents the total positioning error of the end effector of the six-axis charging robot arm in positioning the vehicle interface, reflecting the comprehensive measure of the position deviation of the robot arm in the positioning process;

[0056] i: is the index variable of summation, taking values from 1 to 6, corresponding to the 6 joints of the six-axis charging robot arm, for traversing calculation of the contribution of each joint to the total error;

[0057] f: is generally a function describing the relationship between the position (or pose related to positioning, etc.) of the end effector of the robot arm and the joint variable, that is, obtained through Denavit-Hartenberg parameterization modeling, the mapping function of the end effector pose about the joint variable, which reflects how the change of the joint variable affects the position and other positioning related quantities of the end effector;

[0058] θ i : the joint variable (such as joint angle, etc. depending on the type of robot arm joint and modeling method) of the i-th joint is one of the key parameters determining the position of the end effector of the robot arm;

[0059] △θ i: Change of the i-th joint variable, △θ i <0.01°, which reflects the fluctuation or error in the actual operation of the joint variable, and this fluctuation will be transmitted to the end effector through the kinematics of the robot arm, thereby generating a positioning error;

[0060] : Partial derivative of the function f with respect to the i-th joint variable θ i , which represents the sensitivity of the change of the end effector position (described by f) caused by a unit change of the i-th joint variable θ i , that is, the "transmission coefficient" of the joint variable θ i on the positioning of the end effector. The larger the partial derivative, the more significant the influence of the change of the joint variable on the positioning of the end effector.

[0061] The application adopts a green electricity space-time translation mechanism. During the peak period of photovoltaic power generation from 9:00 to 15:00, the mobile energy storage charging and discharging platform preferentially stores green electricity into the battery energy storage module as a constraint condition of the "peak-valley electricity price difference". During the non-photovoltaic power generation period (such as at night), the "photovoltaic residual electricity + valley electricity" hybrid power supply mode is adopted to reduce the cost of kilowatt-hour.

[0062] Meanwhile, the mobile energy storage charging and discharging platform also supports double charging and double discharging energy management, and the single platform has a daily cycle frequency of greater than or equal to 2 times, and the SOC (state of charge) threshold of the energy storage unit is set to 20% to 90%, so as to avoid the influence of deep charging and discharging on the service life of the battery.

[0063] The mobile energy storage charging and discharging platform is also provided with a multi-vehicle cooperative charging protocol, which supports "alternate charging" of multiple vehicles on the same platform. For example, when vehicle A is charging, the platform is simultaneously moved to the position of vehicle B and completes the preparation for docking, and the overall service efficiency is improved by 40%.

[0064] For vehicle battery replacement, the mechanical grabbing module in the application further comprises a seven-axis battery replacement mechanical arm for battery replacement. The seven-axis battery replacement mechanical arm is provided with a control module, an infrared identification module, a 3D positioning module, and a force control sensor integrated at the end of the seven-axis battery replacement mechanical arm. The seven-axis battery replacement mechanical arm cooperates with the standardized battery replacement position configured in the designated battery replacement area for battery replacement. The infrared identification module and the 3D positioning module position the battery replacement area of the battery replacement vehicle. The control module controls the seven-axis battery replacement mechanical arm to grab the battery replacement battery, and controls the battery replacement docking pressure through the force control sensor to avoid damaging the vehicle. Of course, the application performs visual-force control joint calibration every 500 times of battery replacement to ensure the docking accuracy. Under the battery replacement mode, a single platform can serve 22 two-wheeled vehicles per day.

[0065] As Figure 2As shown, the intelligent scheduling cloud platform in the system of the application adopts a "photovoltaic-energy storage-vehicle" three-level cooperative control model constructed based on a 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 module in the next 24 or 48 hours, realizes ultra-short-term prediction, and the error is less than 5%, can combine the weather data in the next 24 or 48 hours, give accurate analysis of the power generation in a short time, such as whether there is rainy weather in the power generation period of 9-15, so as to budget accurate power generation, and judge in advance the number and maximum range of mobile energy storage charging and swapping platforms that can be used for scheduling;

[0066] The task allocation layer uses an improved ant colony algorithm to dynamically optimize the mobile path of the mobile energy storage charging and swapping platform, and the improved ant colony algorithm used is as follows:

[0067] ;

[0068] wherein: P k ij ( t )‌: represents the probability of ant k moving from node i to node j at time t, which is used to describe the possibility of ants moving from one node to another node when selecting a path;

[0069] T ij (t): the pheromone concentration on the path between node i and node j at time t, pheromone is an important basis for guiding ants to select paths in the ant colony algorithm, ants tend to choose paths with high pheromone concentration, and subsequent pheromone updating mechanism (generally including evaporation, new addition, etc.) is used to dynamically adjust;

[0070] η ij ( t ): the heuristic factor of node i at time t, which is usually related to the "advantage" of the path, such as the reciprocal of the distance from the node to node i (the closer the distance, the greater the heuristic factor, and the ants are more inclined to choose), which is used to guide ants to select better paths and reflect the guiding information of the problem itself to path selection;

[0071] α: the influence factor of pheromone concentration, which is used to control the weight of pheromone concentration in path selection probability calculation, the greater α, the more ants tend to rely on pheromone concentration when selecting paths, preferably α=2;

[0072] β: the influence factor of heuristic factor, which is used to control the weight of heuristic factor in path selection probability calculation, the greater β, the more ants rely on heuristic information (such as distance) when selecting paths, preferably β=5;

[0073] Allowed k : the next node set that the ant k can choose, that is, the set of nodes that the ant has not visited and can transfer to when at node i, limiting the node range of the next step of the ant transfer;

[0074] T is (t)、 η is (t): the meanings are similar to T ij (t)、 η ij (t), but here the pheromone concentration and heuristic factor of node i to the node s in the set Allowed k are used to participate in the summation calculation 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 transfers is 1);

[0075] When alpha=2 and beta=5, the simulation result can improve the path planning efficiency by 37%.

[0076] The user interaction layer adopts an application APP to perform charging demand submission, fee settlement and charging progress visualization, the APP integrates charging reservation, electronic fence and emergency braking function, and shared electric vehicle scene supports automatic order distribution of battery replacement.

[0077] The application preferably interworks the task allocation layer in the intelligent scheduling cloud platform and the vehicle operation platform data, the intelligent scheduling cloud platform acquires real-time positioning data (GPS error <=10m) and state of charge data (SOC threshold <=20% triggers battery replacement request) of each vehicle in the vehicle operation platform through an API interface, and inputs a battery replacement demand prediction model, calculates a high-demand battery replacement area in a future set time period (such as within 1 hour in the future) according to the delineated electronic fence, schedules the corresponding time <=2 minutes; dynamic battery replacement priority calculation is performed on the vehicles in the high-demand battery replacement area, the priority battery replacement vehicles are obtained, and are transmitted to the mobile energy storage charging and battery replacement platform.

[0078] The algorithm for obtaining the high-demand battery replacement area in the battery replacement demand prediction model is:

[0079] ;

[0080] Wherein: alpha, beta and gamma are weight values, alpha+beta+gamma=1;

[0081] SOC(t-1) is the remaining capacity of the electric vehicle battery at t-1 time, the lower the remaining capacity, the higher the demand of the vehicle for battery replacement, so it is an important factor affecting the demand for battery replacement;

[0082] Density(t-1) is the vehicle density of the region at t-1, the higher the vehicle density, the more potential battery swap demand users, the higher the battery swap demand;

[0083] Historical(t) is historical battery swap data or historical load data, by analyzing the past battery swap demand of the region, including the battery swap frequency and the battery swap amount in different time periods, the time regularity and trend of battery swap demand can be mined.

[0084] The dynamic battery swap priority calculation for high demand battery swap regions in the battery swap demand prediction model is as follows:

[0085] ;

[0086] Where: Urgency_i is the vehicle urgency set by the vehicle operation platform, 1 for shared electric vehicle scene, and 0.8 for mine vehicle;

[0087] Distance_i is the distance between the vehicle and the mobile energy storage and charging platform;

[0088] SOC_i is the current state of charge of the vehicle.

[0089] The following is for two battery swap scenarios:

[0090] (1) Shared electric vehicle battery swap

[0091] Interoperate with the operation platform data, get the vehicle location, power, and riding track through the API interface, set the battery swap response time within the electronic fence (radius 500m) ≤10 minutes.

[0092] Standardize the two-wheeled vehicle battery size (300mm x 200mm x 150mm) and interface specification (GB / T 36945-2018), support plug and play.

[0093] (2) Mine unmanned battery swap

[0094] Draw the battery swap area, set the standardized battery swap potential beside the main road in the mine, equip with positioning signboards, and the mobile energy storage and charging platform realizes centimeter-level docking through UWB positioning. UWB (Ultra-Wideband) positioning is a high-precision positioning method based on ultra-wideband wireless communication technology, suitable for precise ranging and positioning.

[0095] In addition, the mobile energy storage and charging 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 each time the battery is swapped, and automatically returns the battery energy storage module exceeding the set threshold to the BIPV photovoltaic power generation module for slow charging repair.

[0096] Taking a cluster of 10 mobile energy storage charging and swapping platforms as an example, the annual service of new energy vehicles can reach 150,000 times (including 50,000 times of battery swapping), corresponding to carbon emission reduction of about 15,000 tons, and the operating cost is reduced by 42% compared with traditional charging stations, and the daily average income of shared electric vehicle operators per vehicle is increased by 83%.

[0097] The comparison of the system of the application with the traditional charging station is shown in the following table:

[0098]

[0099] Next, taking shared electric vehicle battery swapping as an example, the battery swapping process is specifically explained.

[0100] As shown in Figure 4 When the SOC of the electric vehicle is less than or equal to 20%, the electric vehicle generates a power warning information, at this time the vehicle operation platform will receive the warning information, and upload the position and power data of the electric vehicle to the intelligent scheduling cloud platform, predict the demand based on the LSTM algorithm, predict the response in 2 minutes, and optimize the path, at the same time the intelligent scheduling cloud platform sends a scheduling instruction to the mobile energy storage charging and swapping platform (i.e. mobile platform), the mobile platform generates a response and goes to the target position of the electric vehicle, after reaching the battery swapping area of the electric vehicle, the seven-axis battery swapping robot of the mobile platform will perform battery swapping, the battery swapping time is less than or equal to 3 minutes, at the same time the battery swapping data is returned to the vehicle operation platform and the intelligent scheduling cloud platform, and the battery swapping is completed.

[0101] The unmentioned part of the application is applicable to the prior art.

[0102] Obviously, the above embodiments are only examples for clearly illustrating, and not limit the embodiments. For those skilled in the art, on the basis of the above description, other different forms of changes or variations can also be made. Here, it is not necessary and impossible to enumerate all the embodiments. The obvious changes or variations derived therefrom are still within the protection scope of the application.

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 deployed on the roof of a building, a mobile energy storage charging and swapping platform, and an intelligent scheduling cloud platform. 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 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; The intelligent scheduling cloud platform uses a 5G-V2X communication protocol to build a three-level collaborative control model for photovoltaics, energy storage, and vehicles. It 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 for 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; and the user interaction layer uses an application to execute charging demand submission, fee settlement, and charging progress visualization. The task allocation layer in the intelligent scheduling cloud platform communicates with the vehicle operation platform data. 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. According to the demarcated electronic fence, the high-demand battery swap area within the future set time period is calculated. The dynamic battery swap priority calculation is performed for the vehicles in the high-demand battery swap area, and the priority battery swap vehicles are obtained and transmitted to the mobile energy storage charging and swapping platform; The algorithm for obtaining high-demand battery swapping areas in the battery swapping demand prediction model is: Demand(t)=α·SOC(t-1)+β·Density(t-1)+γ·Historical(t); 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; The algorithm for dynamic battery swap priority calculation for high-demand battery swap areas in the battery swap demand prediction model is: Priority_i=0.4·(1-SOC_i)+0.3·Distance_i^(-1)+0.3·Urgency_i 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.

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 the vehicle to the charging point through its own self-powered battery pack to charge the vehicle or drives it 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; 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 displacement of the charging gun to the vehicle charging interface and controls the charging docking pressure through the force control sensor.

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 any one of claims 1 to 3, 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.

5. 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 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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