Hydrogen fuel express delivery vehicle logistics allocation system

Abstract

The invention provides a hydrogen fuel express delivery vehicle logistics allocation system, the allocation system comprises a vehicle control unit, an allocation management module, a hydrogen fuel management system module and a big database, and the invention aims to provide a model selection scheme of a hydrogen fuel cell logistics vehicle and a set of digital tools. On the basis of analysis of real requirements of customer logistics scenes and collection and input of field investigation data, the hydrogen fuel cell logistics vehicles required by scene operation can be accurately matched, and the risk of failure of vehicle type selection caused by insufficient ability and experience of investigation personnel is avoided, so that economic losses brought to vehicle factories and customers are avoided.

Description

Technical Field

[0001] The present invention relates to the field of automobile engineering technology, in particular to the field of hydrogen fuel cell technology. Background Art

[0002] The current hydrogen fuel cell logistics vehicle industry is still in its early stages of development. Due to factors such as the high cost of vehicle manufacturing, high fuel costs, and imperfect hydrogen refueling station infrastructure, hydrogen fuel cell logistics vehicles are difficult to mass-produce. They need to be customized in design and development based on the customer's actual logistics scenarios, and produced and delivered in small batches.

[0003] Many hydrogen fuel cell logistics vehicle manufacturing companies are new forces. They are unfamiliar with customer logistics scenarios and have no professional grasp of logistics operation processes and specifications. As a result, they are unable to fully collect information and accurately understand customer vehicle demand when conducting vehicle demand surveys.

[0004] When conducting research on customer logistics scenarios, vehicle manufacturers and operating companies generally still use the most traditional interview and on-site survey model. They lack detailed and standardized research forms, templates, data collection methods and strategies, and overly rely on the professional ability, experience and on-the-spot performance of researchers, resulting in insufficient and inaccurate research and missing collected data.

[0005] Based on the data and information collected from the survey, it requires high professional knowledge, experience and tools to derive or calculate the parameters of each component of the vehicle. The current common method still requires experts to use manual or simple, decentralized tools to roughly evaluate or calculate relevant configuration parameters. This method is also overly dependent on expert experience and ability, which is difficult to be responsible for and the accuracy is difficult to evaluate, and there is a large degree of uncertainty.

[0006] Currently, the vehicle model library data of vehicle manufacturers basically only stores basic configuration information. Experts are needed to select the intended models one by one according to the required component parameters and compare them item by item, and manually evaluate the matching degree of the models. This is also overly dependent on the experience and ability of experts. The matching degree is difficult to quantify and inefficient, and it is difficult to give an objective evaluation.

[0007] Due to the small number of hydrogen vehicles in operation and the limited logistics scenarios they cover, most vehicle manufacturers and operating companies have relatively little data accumulation, which leads to insufficient understanding of the performance, failure rate, cost, etc. of hydrogen vehicles, which also affects the accuracy of vehicle selection.

[0008] Through the analysis of the above pain points, the lack of standardized and complete research tools and templates, the lack of configuration parameter calculation tools, the lack of matching decision analysis tools and the support of hydrogen vehicle operation data directly affect the accuracy of vehicle selection, which will bring greater risks to subsequent customers' vehicle use costs, loading requirements, transportation timeliness and transportation distance, and may even directly lead to serious consequences such as vehicle delivery failure or vehicle return.

[0009] In order to solve the above pain points, a complete set of digital tools, templates and systems are urgently needed to solve the dependence on expert capabilities and experience in all aspects from research, data processing, parameter calculation, vehicle model library and vehicle model intelligent matching, and realize capability replication, precise selection and data empowerment. Summary of the invention

[0010] The present invention proposes a logistics dispatching system for hydrogen fuel express vehicles, which aims to solve key technical problems such as vehicle operation efficiency and dispatch optimization, hydrogen fuel management and supply, intelligent monitoring and early warning, and response to traffic congestion and climate impact. By integrating the vehicle control unit, dispatching management module and big database, the system realizes efficient management and route planning of vehicles, while ensuring the timely supply of hydrogen fuel. The system uses real-time monitoring and early warning functions to dynamically adjust driving routes to cope with congestion and climate change, and optimizes transportation efficiency and safety through data-driven decision support, providing effective support for the application of hydrogen fuel vehicles in modern logistics.

[0011] A hydrogen fuel express vehicle logistics dispatching system, the dispatching system comprises a vehicle control unit, a dispatching management module, a hydrogen fuel management system module and a big database; wherein the signal output end of the vehicle control unit is connected to the signal input end of the big database, the vehicle signal output end of the vehicle control unit is connected to the vehicle signal input end of the dispatching management module, and the vehicle energy signal output end of the vehicle control unit is connected to the vehicle energy signal input end of the hydrogen fuel management system module.

[0012] Preferably, the vehicle control unit includes a vehicle positioning device, a vehicle status monitoring device, a remote control device and an early warning device; wherein the position signal output end of the vehicle positioning device is connected to the position signal input end of the vehicle control unit, the status signal output end of the vehicle status monitoring device is connected to the status signal input end of the vehicle control unit, the control signal output end of the remote control device is connected to the control signal input end of the vehicle control unit, and the fault signal output end of the early warning device is connected to the fault signal input end of the vehicle control unit.

[0013] Preferably, the deployment management module includes a task receiving and assigning unit, a path planning and optimization unit, a real-time scheduling and monitoring unit and a data analysis unit; wherein the signal input end of the task receiving and assigning unit is connected to the signal output end of the deployment management module, the road signal input unit of the path planning and optimization unit is connected to the road signal output unit of the deployment management module, the signal input end of the real-time scheduling and monitoring unit is connected to the signal output end of the deployment management module, and the data signal input end of the data analysis unit is connected to the data signal output end of the deployment management module.

[0014] Preferably, the hydrogen fuel management system module includes a hydrogen storage unit, a compression unit, a hydrogenation unit and a control unit; wherein the signal input end of the hydrogen storage unit is connected to the signal output end of the hydrogen fuel management system module, the hydrogenation signal output end of the hydrogen storage unit is connected to the hydrogenation signal input end of the compression unit, the hydrogenation signal output end of the compression unit is connected to the hydrogenation unit input end of the hydrogenation unit, the hydrogenation signal output end of the hydrogenation unit is connected to the hydrogenation signal input end of the control unit, and the hydrogenation signal output end of the control unit is connected to the hydrogenation signal input end of the hydrogen fuel management system module.

[0015] Preferably, the large database includes a vehicle type database, a cargo type database and a hydrogen fuel cell vehicle operation database; wherein the signal output end of the cargo type database is connected to the signal input end of the vehicle type database, and the signal output end of the vehicle type database is connected to the signal input end of the hydrogen fuel cell vehicle operation database.

[0016] Preferably, the hydrogen fuel management system module realizes the real-time supply of hydrogen fuel vehicles through intelligent hydrogen storage and hydrogenation units, and its working method is divided into the following steps:

[0017] S1: The hydrogen fuel management system module compresses hydrogen through a compression unit to increase the pressure of hydrogen and transports the hydrogen to a hydrogen storage unit;

[0018] S2: The hydrogen fuel management system module converts the hydrogen into a solid compound by reacting the alloy in the hydrogen storage unit with the hydrogen, and stores the hydrogen in the hydrogen storage unit;

[0019] S3: When the hydrogen fuel management system module receives a hydrogenation request, the hydrogen fuel management system module completes rapid hydrogenation through a hydrogenation unit.

[0020] Preferably, in S3, the hydrogen storage unit heats the alloy in the hydrogen storage unit to convert the solid compound back into gaseous hydrogen, and the gaseous hydrogen is then transported to the hydrogen fuel vehicle through the hydrogenation unit.

[0021] Preferably, in S3, when the hydrogen fuel management system module completes the rapid hydrogenation through the hydrogenation unit, the control unit of the hydrogen fuel management system module monitors the hydrogen content in the hydrogen fuel vehicle in real time, and dynamically adjusts the hydrogenation rate of the hydrogenation unit according to the hydrogen content in the hydrogen fuel vehicle until the hydrogen in the hydrogen fuel vehicle is full.

[0022] Preferably, the operation of the deployment management module is divided into the following steps:

[0023] Step 1: The task receiving and assigning unit receives the transport task, selects the corresponding vehicle type according to the transport distance and the weight of the transported goods, and forms a preliminary plan;

[0024] Step 2: The path planning and optimization unit forms a preliminary driving route according to the preliminary plan, and then obtains the road condition information of the current driving route according to the real-time traffic information technology, and generates an alternative route at the same time;

[0025] Step 3: The real-time dispatching and monitoring unit obtains the battery information of the vehicle. When the battery of the vehicle is less than 10%, the real-time dispatching and monitoring unit issues an alarm, automatically arranges other vehicles for support, and communicates with the hydrogen fuel management system module to arrange the vehicle to go to the nearest hydrogen refueling station for hydrogen refueling;

[0026] Step 4: The real-time dispatching and monitoring unit obtains vehicle route information. When the vehicle's driving route ahead is congested, the real-time dispatching and monitoring unit automatically adjusts the transportation route.

[0027] Preferably, the dispatch management module selects the most suitable road for the transportation distance, the time spent, the total weight, the blocking weight and the climate weight, and the evaluation level is J, and the formula is as follows:

[0028]

[0029] Among them, the speed weight indicates the degree to which the vehicle speed is affected by the road speed limit, and its formula is:

[0030]

[0031] Among them, K represents the speed weight (unit: m / s), n represents the number of sections with different speed limits, and L i represents the distance of the i-th speed limit section, t i represents the time required to complete the i-th speed limit section, V i represents the speed limit value of the i-th speed limit section;

[0032] The climate weight T indicates the degree to which the vehicle is affected by the weather, and the climate weight T is normalized and is a dimensionless coefficient, and its value range is 1-2. When the weather has no effect on the vehicle's driving, the value of T is 2, and T is affected by the weather.

[0033] The gross weight g represents the sum of the weight of the vehicle and the cargo;

[0034] The blocking weight Q represents a value reflecting the traffic congestion situation, and the blocking weight Q is a dimensionless coefficient after normalization, and the value range of the blocking weight is 1-2. When the blocking weight is 1, it means that there is no congestion on the road ahead, and Q increases with the impact of the congestion ahead;

[0035] When 3×10 4 <J<9×10 4 , it indicates that the dispatch management module determines that the road ahead is seriously congested or the weather has a great impact on vehicle driving, or both, and thus selects an alternate route;

[0036] When 9×10 4 ≤J<<1.×10 5 When , it means that the congestion ahead is light or there is no congestion and the weather has little impact on vehicle driving, thereby guiding the vehicle to continue moving forward.

[0037] The beneficial effects of the present invention are as follows: the 50-80 parameter indicators required for traditional selection are expanded to more than 200, and the calculation rules are precisely defined, so that the selection is more accurate and the risk of selection errors is greatly avoided; in the past, selection required the use of multiple calculation tools to calculate each item, and then manually evaluate the matching degree. Through the tool set and evaluation report of the present invention, the selection time can be shortened from 3 days to 15 minutes; in the past, vehicle selection required at least 5 years of experienced product / technical personnel to make a good selection. Relying on the system tools of the present invention, sales managers with more than 2 years of experience can complete data collection, and the system automatically performs selection evaluation, which lowers the selection threshold. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is the operation and deployment system of the hydrogen-powered express delivery vehicle of the present invention;

[0039] Figure 2 The vehicle control unit of the present invention;

[0040] Figure 3 The deployment management module of the present invention;

[0041] Figure 4 The hydrogen fuel management system module of the present invention;

[0042] Figure 5 This is the large database mentioned in the present invention. DETAILED DESCRIPTION

[0043] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0044] One embodiment of the present invention is a hydrogen fuel express vehicle logistics allocation system, which includes a vehicle control unit, a allocation management module, a hydrogen fuel management system module and a big database; wherein the signal output end of the vehicle control unit is connected to the signal input end of the big database, the vehicle signal output end of the vehicle control unit is connected to the vehicle signal input end of the scheduling management module, and the vehicle energy signal output end of the vehicle control unit is connected to the vehicle energy signal input end of the hydrogen fuel management system module.

[0045] The working principle and effect of the above technical solution are as follows: the present invention fully investigates the vehicles, goods, warehouses, yards and transportation operations included in various logistics scenarios, collects and analyzes data in different dimensions on the links such as goods attributes, packaging / transferring, loading and unloading, storage, sorting, processing and transportation, and establishes a label library according to different dimensions such as business type, transportation type, asset type, transportation scope, operation route, and goods attributes. By deconstructing and analyzing various types of vehicle models from 20+ categories and 200+ parameter indicators (such as fuel cells, power batteries, hydrogen systems, drive axles, suspension systems, upper systems, performance parameters, size parameters, etc.), it is different from the traditional approach (only listing parameter configurations) in that the scope of application and selection rules of each parameter indicator are expanded, the vehicle model is more refined and accurately defined, and a vehicle model parameter configuration data set is formed. According to the data collected from the survey, combined with professional knowledge in the fields of automotive engineering technology, fuel cell selection technology, hydrogen system selection technology, materials science, mechanics, etc., a set of parameter calculation tools for hydrogen energy vehicles and parts is formed. For example, the size, weight and material (ordinary steel or high-strength steel) of the cargo box are calculated according to the cargo attributes, weight, volume, loading and unloading methods, and loading and unloading positions; the power range and energy consumption level of the fuel cell stack are evaluated according to the load, road conditions, and speed distribution; according to the data collected in the survey, the results calculated by the calculation tool set are defined using the component parameters; according to the set matching rules, the model that best meets the set rules is found from the model library, and the matching scores of each dimension index are given to form a model matching report to guide whether the selection results are directly available or customized to the manufacturer. The 50-80 parameter indicators required for traditional selection are expanded to more than 200, and the calculation rules are precisely defined, making the selection more accurate and greatly avoiding the risk of selection errors; in the past, the selection required the use of a variety of calculation tools to calculate each item, and then manually evaluate the matching degree. Through the tool set and evaluation report of the present invention, the selection time can be shortened from 3 days to 15 minutes; in the past, vehicle selection required at least 5 years of experienced product / technical personnel to make a good selection. Relying on the system tool of the present invention, only sales managers with more than 2 years of experience can complete data collection, and the system automatically performs selection evaluation, which reduces the selection threshold.

[0046] In one embodiment of the present invention, the vehicle control unit includes a vehicle positioning device, a vehicle status monitoring device, a remote control device and an early warning device; wherein the position signal output end of the vehicle positioning device is connected to the position signal input end of the vehicle control unit, the status signal output end of the vehicle status monitoring device is connected to the status signal input end of the vehicle control unit, the control signal output end of the remote control device is connected to the control signal input end of the vehicle control unit, and the fault signal output end of the early warning device is connected to the fault signal input end of the vehicle control unit.

[0047] The working principle and effect of the above technical solution are as follows: the vehicle positioning device uses GPS to receive wireless signals containing vehicle location information, and after parsing the wireless signals, determines the longitude, latitude and time information of the vehicle, and transmits the parsed location information to the dispatch management module through a wireless communication network (such as a 4G / 5G network). The vehicle status monitoring unit collects various parameters of the vehicle in real time through sensors installed on the vehicle, such as vehicle speed, rotation speed, hydrogen fuel content, etc., and then converts the data collected by these sensors into electrical signals and transmits them to the early warning unit. The signal processor in the early warning unit processes and analyzes the data collected by the sensors, and uses advanced algorithms and machine learning techniques to compare the perceived vehicles with the preset vehicle models to determine their types, driving directions and speeds, etc. Through such identification and analysis, the system can determine whether there is a potential risk of collision or other dangerous situations. Once the system identifies a potential risk of collision or other dangerous situations, it will immediately warn the driver through alarms, vibrating seats, sounds, etc. These warnings are usually immediate so that the driver can react in time and take measures to avoid danger. If the driver does not take appropriate measures, the system can also intervene, such as automatically reducing the speed of the vehicle or reducing the engine output power through the automatic braking system to avoid or reduce the severity of the collision. The remote control unit can remotely operate the vehicle to start and stop after receiving instructions; the vehicle control unit can monitor the location and status of the vehicle in real time to ensure that the vehicle is fully utilized and reduce idle time, thereby improving overall transportation efficiency. By optimizing scheduling resources, the system can reasonably allocate vehicle and driver resources according to demand and actual conditions to ensure the safety and efficiency of cargo transportation. The vehicle control unit can monitor the location and route of the vehicle in real time, and display the specific location of the vehicle through a map to help managers ensure that the vehicle is heading in the right direction and deliver the goods at the scheduled time. The system can monitor the route and location of the vehicle, prevent the vehicle from being lost or stolen, and provide real-time security. Vehicle management software is developed not only to ensure that each vehicle is in good working condition, but also to ensure the safety of the people driving these vehicles. The system can remind drivers of potential dangerous situations and reduce the occurrence of accidents. The vehicle control unit can provide detailed reports to let enterprises understand the vehicle usage status and ensure that the vehicle usage meets the enterprise management requirements. The system can automatically record vehicle mileage, fuel consumption and other information to help enterprises better manage and analyze vehicles. The vehicle control unit can provide better decision support through intelligent analysis of vehicle usage, help enterprises to carry out refined management and optimize resource allocation.

[0048] According to one embodiment of the present invention, the dispatching management module includes a task receiving and assigning unit, a path planning and optimization unit, a real-time scheduling and monitoring unit, and a data analysis unit; wherein the signal input end of the task receiving and assigning unit is connected to the signal output end of the dispatching management module, the road signal input unit of the path planning and optimization unit is connected to the road signal output unit of the dispatching management module, the signal input end of the real-time scheduling and monitoring unit is connected to the signal output end of the dispatching management module, and the data signal input end of the data analysis unit is connected to the data signal output end of the dispatching management module.

[0049] The working principle and effect of the above technical solution are as follows: the task receiving and assigning unit will first receive task requests from different sources, and the unit will parse the received task requests to extract key information, such as task type, starting location, destination, estimated completion time, special requirements, etc. The parsed task information will be stored in the system's database for subsequent task assignment and query; the task assignment unit will select appropriate tasks from the task queue for assignment based on the preset scheduling strategy and algorithm, and the unit will consider factors such as the vehicle's current location, status, remaining carrying capacity, as well as the urgency of the task, distance, estimated completion time, etc., to match the vehicle with the task. Based on the results of resource matching, the unit will make an allocation decision and assign the task to the most suitable vehicle. Once the allocation decision is determined, the unit will send the task information to the corresponding vehicle and notify the vehicle to go to the designated location to perform the task. Maximum load = unit vehicle full load weight * number of full load vehicles in the vehicle, Before the mission begins, the path planning unit will select an optimal path and adjust the path in real time by determining the feasibility of the road ahead while the vehicle is moving; the dispatching management module reduces driving time and costs, improves transportation efficiency, and achieves unified management of vehicles through real-time monitoring and path optimization, reduces manual intervention, reduces management costs, and realizes intelligent scheduling and decision-making based on big data and artificial intelligence technology, thereby improving management level and efficiency.

[0050] In one embodiment of the present invention, the hydrogen fuel management system module includes a hydrogen storage unit, a compression unit, a hydrogenation unit and a control unit; wherein the signal input end of the hydrogen storage unit is connected to the signal output end of the hydrogen fuel management system module, the hydrogenation signal output end of the hydrogen storage unit is connected to the hydrogenation signal input end of the compression unit, the hydrogenation signal output end of the compression unit is connected to the hydrogenation unit input end of the hydrogenation unit, the hydrogenation signal output end of the hydrogenation unit is connected to the hydrogenation signal input end of the control unit, and the hydrogenation signal output end of the control unit is connected to the hydrogenation signal input end of the hydrogen fuel management system module.

[0051] The working principle and effect of the above technical solution are as follows: high-purity hydrogen is transported from outside the station or produced inside the station after purification, and compressed to a certain pressure through the hydrogen compression system. The pressurized hydrogen is stored in a fixed high-pressure container. When hydrogen needs to be refilled, the hydrogen is quickly filled into the on-board hydrogen storage container through the filling system under the action of the high pressure difference between the fixed high-pressure container of the hydrogen station and the on-board hydrogen storage container. The hydrogenation equipment provides hydrogen to hydrogen fuel cell vehicles through hydrogenation machines, hydrogen metering units and other equipment according to vehicle needs. During the hydrogenation process, the control unit will monitor parameters such as hydrogen flow and pressure in real time to ensure the safety and reliability of the hydrogenation process. Integrated management and control can achieve comprehensive monitoring and management of all aspects of hydrogen energy production, storage, transportation and utilization, and improve the efficiency and safety of energy management. Through big data analysis and artificial intelligence technology, the system can analyze data in real time and provide accurate information support to decision makers, thereby optimizing operational decisions. The hydrogen fuel management system module reduces the need for manual intervention and reduces management costs through automated and intelligent management methods. By mining and analyzing historical data, enterprises can further optimize safety management measures and improve safety management levels, thereby indirectly reducing management costs. Through real-time monitoring and control, safety hazards can be discovered in a timely manner, and effective measures can be taken to eliminate them, reducing the risk of accidents. The system has built-in target responsibility management and assessment and review management modules to ensure that production responsibility targets are clear, rewards and punishments are clear, and the level of safety management is further improved.

[0052] In one embodiment of the present invention, the large database includes a vehicle type database, a cargo type database and a hydrogen fuel cell vehicle operation database; wherein the signal output end of the cargo type database is connected to the signal input end of the vehicle type database, and the signal output end of the vehicle type database is connected to the signal input end of the hydrogen fuel cell vehicle operation database.

[0053] The working principle and effect of the above technical solution are as follows: the vehicle type database stores detailed information of various types of logistics vehicles, such as vehicle model, load capacity, volume limit, fuel consumption, etc. This information is usually organized in the form of a table, with each row representing a vehicle and each column representing an attribute of the vehicle. New vehicle information is entered into the database through data definition language (DDL) or data manipulation language (DML). When vehicle information changes (such as maintenance, upgrade, etc.), the database management system (DBMS) will update the corresponding records. The cargo type database stores detailed information of various types of cargo, such as cargo name, classification, weight, volume, transportation requirements, etc. It is also organized in a table form, and each cargo is uniquely identified by a primary key (such as cargo ID). The hydrogen fuel cell vehicle operation database stores data such as the operating status, driving trajectory, energy consumption, and hydrogen consumption of hydrogen fuel cell vehicles. The operating data of hydrogen fuel cell vehicles is collected in real time through sensors and Internet of Things technology. The collected data is cleaned and integrated to ensure data quality and consistency. The vehicle model database records the information of various types of logistics vehicles in detail, such as load capacity, volume restrictions, etc., which helps logistics companies choose the most suitable vehicle model according to the specific needs of the goods, optimize resource allocation, and improve transportation efficiency. Through the vehicle model database, logistics companies can monitor the use of vehicles in real time, such as idle time, maintenance records, etc., so as to more accurately dispatch and manage vehicles, reduce vehicle idle time, and reduce operating costs. The vehicle model database provides rich data support. Logistics companies can understand the operating status of vehicles by analyzing vehicle usage data, and provide decision-making basis for future vehicle procurement, maintenance and updates. The cargo type database classifies and describes various types of goods in detail, which helps logistics companies to formulate more accurate transportation plans based on the attributes of goods and improve transportation safety and efficiency. Through the cargo type database, logistics companies can quickly query relevant information about goods, such as transportation requirements, packaging requirements, etc., so as to quickly respond to customer needs and improve customer satisfaction. The cargo type database can support the needs of inventory management. By recording information such as the type, quantity, and storage location of goods, it helps logistics companies to achieve refined inventory management and reduce inventory costs. The hydrogen fuel cell tram operation database can monitor the tram's operating status, energy consumption, hydrogen consumption and other data in real time, provide real-time data support for the tram's dispatch and maintenance, and ensure the normal operation of the tram. By analyzing the hydrogen fuel cell tram's operating data, logistics companies can understand the tram's energy consumption and provide a basis for optimizing energy use and reducing operating costs. At the same time, it can also provide data support for the research and development and improvement of hydrogen fuel cell trams. As a clean energy vehicle, the collection and analysis of hydrogen fuel cell tram's operating data helps to evaluate its performance in environmental protection and sustainability, and provide support for the green development of the logistics industry.

[0054] In one embodiment of the present invention, the hydrogen fuel management system module realizes the real-time supply of hydrogen fuel vehicles through intelligent hydrogen storage and hydrogenation units, and its working method is divided into the following steps:

[0055] S1: The hydrogen fuel management system module compresses hydrogen through a compression unit to increase the pressure of hydrogen and transports the hydrogen to a hydrogen storage unit;

[0056] S2: The hydrogen fuel management system module converts the hydrogen into a solid compound by reacting the alloy in the hydrogen storage unit with the hydrogen, and stores the hydrogen in the hydrogen storage unit;

[0057] S3: When the hydrogen fuel management system module receives a hydrogenation request, the hydrogen fuel management system module completes rapid hydrogenation through a hydrogenation unit.

[0058] The working principle and effect of the above technical solution are as follows: the dispatch management module first collects various data related to the transportation task, including the total weight of the goods, the location information of the starting and ending points, the estimated departure and arrival time, etc. At the same time, the system will also integrate real-time road condition information, including the road blocking weight, traffic flow, accident conditions, etc. Weather data is also an important factor considered by the system, including temperature, precipitation, wind speed, etc., which will affect the safety and efficiency of transportation. Based on the collected data, the dispatch management module will perform route planning. By considering the total weight of the goods and the transportation distance, the system will screen out vehicles that can carry these goods and plan a preliminary transportation route. Next, the system will analyze the time spent on different routes. This includes driving time, waiting time, and possible delay time. The blocking weight is a key indicator in this analysis, which reflects the traffic conditions of different sections of the road. On this basis, the system will further consider the climate weight. Severe weather conditions may increase the risk and uncertainty of transportation, so the system needs to evaluate the impact of weather on transportation and adjust the route planning accordingly. After comprehensively considering all factors, the dispatch management module will generate multiple feasible transportation plans. Each plan details the estimated transportation time, cost, and possible risks. The system evaluates and compares these plans based on preset algorithms and strategies. These algorithms may be based on different optimization goals such as minimizing costs, minimizing time, or minimizing risks. Ultimately, the system selects the most suitable transportation route and generates corresponding dispatch instructions. These instructions detail the vehicle's route, expected arrival time, and matters that need attention. During the transportation process, the dispatch management module monitors the vehicle's driving status and location information in real time. By combining with the vehicle's GPS system or other positioning technology, the system can understand the vehicle's driving conditions in real time. If there is traffic congestion, accidents, or other abnormal situations, the system will immediately make adjustments. This may include re-planning the route, adjusting the driving speed, or notifying the driver to take appropriate measures. Through real-time monitoring and adjustments, the dispatch management module can ensure that the transportation task can be completed on time and safely.

[0059] In one embodiment of the present invention, the dispatch management module selects the most suitable road based on the transportation distance, time spent, total weight, congestion weight and climate weight, and the evaluation level is J, and the formula is as follows:

[0060]

[0061] Among them, the speed weight indicates the degree to which the vehicle speed is affected by the road speed limit, and its formula is:

[0062]

[0063] Among them, K represents the speed weight (unit: m / s), n represents the number of sections with different speed limits, and Li represents the distance of the i-th speed limit section, t i represents the time required to complete the i-th speed limit section, V i represents the speed limit value of the i-th speed limit section;

[0064] The climate weight T indicates the degree to which the vehicle is affected by the weather, and the climate weight T is normalized and is a dimensionless coefficient, and its value range is 1-2. When the weather has no effect on the vehicle's driving, the value of T is 2, and T is affected by the weather.

[0065] The gross weight g represents the sum of the weight of the vehicle and the cargo;

[0066] The blocking weight Q represents a value reflecting the traffic congestion situation, and the blocking weight Q is a dimensionless coefficient after normalization, and the value range of the blocking weight is 1-2. When the blocking weight is 1, it means that there is no congestion on the road ahead, and Q increases with the impact of the congestion ahead;

[0067] When 3×10 4 <J<9×10 4 , it indicates that the dispatch management module determines that the road ahead is seriously congested or the weather has a great impact on vehicle driving, or both, and thus selects an alternate route;

[0068] When 9×10 4 ≤J<<1.×10 5 When , it means that the congestion ahead is light or there is no congestion and the weather has little impact on vehicle driving, thereby guiding the vehicle to continue moving forward.

[0069] The working principle and effect of the above technical solution are: the system collects local weather data in real time or regularly from meteorological departments, Internet meteorological services or specialized weather data providers. The collected weather data include temperature, humidity, wind speed, wind direction, precipitation (such as rain, snowfall), visibility, etc. The system analyzes the collected weather data and evaluates their potential impact on vehicle transportation.

[0070] According to different weather conditions, a weight or coefficient is assigned to each weather parameter. For example, severe weather (such as heavy rain, heavy snow, strong wind, etc.) may cause slippery roads and reduced visibility, thereby increasing the risk of accidents, and thus reduce the corresponding climate weights. These coefficients are usually quantified into specific values. The coefficient for sunny days is 2, light rain corresponds to 1.8, and heavy snow corresponds to 1.2; the system integrates all relevant climate weights into a comprehensive climate weight. When planning transportation routes or dispatching vehicles, the system will consider the comprehensive climate weight. Low climate weights may mean that longer routes, safer roads, or transportation time need to be adjusted. The system collects road congestion data in real time, which comes from traffic monitoring cameras, GPS positioning devices, mobile phone signal data, etc. The collected congestion data includes traffic flow, average speed, accident reports, road construction information, etc. The system analyzes the collected congestion data and evaluates the degree of road congestion. According to indicators such as traffic flow and average speed, a blocking weight is assigned to each road section. The congestion weight can be expressed as the degree of deviation of the traffic conditions of the road section from the normal conditions. These coefficients are also quantified into specific values. For example, the coefficient corresponding to the unblocked section is 1, the coefficient corresponding to the light congestion is 1.2, and the coefficient corresponding to the severe congestion is 2. The system integrates the congestion weights of all relevant sections into the overall transportation route evaluation. When planning transportation routes or dispatching vehicles, the system will give priority to roads with lower congestion weights. Low congestion weights mean shorter transportation time, lower fuel consumption and less vehicle wear and tear. By collecting and analyzing weather and congestion data in real time, the system can provide dispatchers with instant decision support. Dispatchers can quickly adjust transportation plans based on climate weights and congestion weights and choose the best transportation route to avoid delays caused by congestion and bad weather. The system can automatically plan routes based on weather and congestion conditions to reduce vehicle idle mileage and waiting time. By optimizing the dispatching algorithm, the system can pair vehicles with close distances and similar tasks to further improve transportation efficiency. The system can warn of potential risks and hidden dangers in advance based on climate weights and congestion weights, such as slippery roads, low visibility, and traffic congestion. Dispatchers can take corresponding measures based on these early warning information to ensure transportation safety. The system can monitor the location, speed, status and other information of the vehicle in real time, and promptly alarm when abnormal situations occur. This helps dispatchers to quickly discover and deal with problems and ensure the safety of drivers and goods. By introducing climate weights and congestion weights, the vehicle dispatch management module can make data-driven decisions. This makes decisions more scientific, reasonable and effective, and helps to improve the performance and efficiency of the entire transportation system. The system can reasonably arrange vehicle travel according to weather and congestion conditions and improve vehicle utilization. This helps to reduce vehicle idleness and reduce resource waste.

[0071] On urban roads, the average speed of vehicles is 60 m / s. Combined with the average vehicle load of 1000 kg, under the worst conditions, that is, bad weather (T = 1) and severe congestion (Q = 2), we can derive a minimum value of this formula, J = 3 × 10 4 When light rain (T = 1.8) has little impact on vehicle travel and the congestion level is light (Q = 1.2), J = 9 × 10 4 , indicating that although there is congestion and rain at this time, it does not affect the normal driving of vehicles. Therefore, when 3×10 4 <J<9×10 4 When , it means that the dispatch management module determines that the road ahead is seriously congested or the weather has a great impact on vehicle driving, or both, and then selects an alternative route. When the weather is clear (T=1) and the road is unobstructed (Q=1), J=1.2×10 5 , when 9×10 4 ≤J<<1.×10 5 When , it means that the congestion ahead is light or there is no congestion and the weather has little impact on vehicle driving, thus guiding the vehicle to continue moving forward. This formula provides a comprehensive traffic condition assessment mechanism by integrating four key parameters: speed weight, climate weight, total weight and congestion weight. The introduction of mass in the formula is because multiplying the speed weight and mass is actually calculating the momentum of the vehicle. The heavier the weight, the longer it takes for the vehicle to accelerate to the same speed under the same power; the maximum speed allowed on a certain section of road combined with the mass of the vehicle affects the overall completion time and efficiency of the transportation task. Combining these two factors can help more accurately predict the actual performance of the vehicle under road conditions. In addition, larger mass and higher speed requirements usually mean higher energy consumption. This formula can also provide a basis for the vehicle to adopt appropriate routes and speeds to optimize fuel consumption and improve economic benefits. In summary, by combining the mass factor with speed, the dynamic driving ability of the vehicle under various traffic conditions can be better evaluated.

[0072] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A hydrogen fuel express vehicle logistics deployment system, characterized in that: The deployment system includes a vehicle control unit, a deployment management module, a hydrogen fuel management system module and a big database; wherein the signal output end of the vehicle control unit is connected to the signal input end of the big database, the vehicle signal output end of the vehicle control unit is connected to the vehicle signal input end of the scheduling management module, and the vehicle energy signal output end of the vehicle control unit is connected to the vehicle energy signal input end of the hydrogen fuel management system module.

2. A blending system according to claim 1, characterized in that: The vehicle control unit includes a vehicle positioning device, a vehicle status monitoring device, a remote control device and an early warning device; wherein the position signal output end of the vehicle positioning device is connected to the position signal input end of the vehicle control unit, the status signal output end of the vehicle status monitoring device is connected to the status signal input end of the vehicle control unit, the control signal output end of the remote control device is connected to the control signal input end of the vehicle control unit, and the fault signal output end of the early warning device is connected to the fault signal input end of the vehicle control unit.

3. A blending system according to claim 1, characterized in that: The deployment management module includes a task receiving and assigning unit, a path planning and optimization unit, a real-time scheduling and monitoring unit, and a data analysis unit; wherein the signal input end of the task receiving and assigning unit is connected to the signal output end of the deployment management module, the road signal input unit of the path planning and optimization unit is connected to the road signal output unit of the deployment management module, the signal input end of the real-time scheduling and monitoring unit is connected to the signal output end of the deployment management module, and the data signal input end of the data analysis unit is connected to the data signal output end of the deployment management module.

4. A blending system according to claim 1, characterized in that: The hydrogen fuel management system module includes a hydrogen storage unit, a compression unit, a hydrogenation unit and a control unit; wherein the signal input end of the hydrogen storage unit is connected to the signal output end of the hydrogen fuel management system module, the hydrogenation signal output end of the hydrogen storage unit is connected to the hydrogenation signal input end of the compression unit, the hydrogenation signal output end of the compression unit is connected to the hydrogenation unit input end of the hydrogenation unit, the hydrogenation signal output end of the hydrogenation unit is connected to the hydrogenation signal input end of the control unit, and the hydrogenation signal output end of the control unit is connected to the hydrogenation signal input end of the hydrogen fuel management system module.

5. A blending system according to claim 1, characterized in that: The large database includes a vehicle type database, a cargo type database and a hydrogen fuel cell vehicle operation database; wherein the signal output end of the cargo type database is connected to the signal input end of the vehicle type database, and the signal output end of the vehicle type database is connected to the signal input end of the hydrogen fuel cell vehicle operation database.

6. A blending system according to claim 1, characterized in that: The hydrogen fuel management system module realizes the real-time supply of hydrogen fuel vehicles through intelligent hydrogen storage and hydrogenation units. Its working method is divided into the following steps: S1: The hydrogen fuel management system module compresses hydrogen through a compression unit to increase the pressure of hydrogen and transports the hydrogen to a hydrogen storage unit; S2: The hydrogen fuel management system module converts the hydrogen into a solid compound by reacting the alloy in the hydrogen storage unit with the hydrogen, and stores the hydrogen in the hydrogen storage unit; S3: When the hydrogen fuel management system module receives a hydrogenation request, the hydrogen fuel management system module completes rapid hydrogenation through a hydrogenation unit.

7. A blending system according to claim 6, characterized in that: In S3, the hydrogen storage unit heats the alloy in the hydrogen storage unit to convert the solid compound back into gaseous hydrogen, and the gaseous hydrogen is then transported to the hydrogen fuel vehicle through the hydrogenation unit.

8. A blending system according to claim 6, characterized in that: In S3, during the process of the hydrogen fuel management system module completing rapid hydrogenation through the hydrogenation unit, the control unit of the hydrogen fuel management system module monitors the hydrogen content in the hydrogen fuel vehicle in real time, and dynamically adjusts the hydrogenation rate of the hydrogenation unit according to the hydrogen content in the hydrogen fuel vehicle until the hydrogen in the hydrogen fuel vehicle is full.

9. The deployment management module according to claim 3, characterized in that: The working method of the deployment management module is divided into the following steps: Step 1: The task receiving and assigning unit receives the transport task, selects the corresponding vehicle type according to the transport distance and the weight of the transported goods, and forms a preliminary plan; Step 2: The path planning and optimization unit forms a preliminary driving route according to the preliminary plan, and then obtains the road condition information of the current driving route according to the real-time traffic information technology, and generates an alternative route at the same time; Step 3: The real-time dispatching and monitoring unit obtains the battery information of the vehicle. When the battery of the vehicle is less than 10%, the real-time dispatching and monitoring unit issues an alarm, automatically arranges other vehicles for support, and communicates with the hydrogen fuel management system module to arrange the vehicle to go to the nearest hydrogen refueling station for hydrogen refueling; Step 4: The real-time dispatching and monitoring unit obtains vehicle route information. When the vehicle's driving route ahead is congested, the real-time dispatching and monitoring unit automatically adjusts the transportation route.

10. The deployment management module according to claim 3, characterized in that: The dispatch management module will select the most suitable road based on the transportation distance, time spent, total weight, congestion weight and climate weight, with the evaluation level being J, and the formula is as follows: Among them, the speed weight indicates the degree to which the vehicle speed is affected by the road speed limit, and its formula is: Among them, K represents the speed weight (unit: m / s), n represents the number of sections with different speed limits, and L i represents the distance of the i-th speed limit section, t i represents the time required to complete the i-th speed limit section, V i Indicates the speed limit value of the i-th speed limit section; The climate weight T indicates the degree to which the vehicle is affected by the weather, and the climate weight T is normalized and is a dimensionless coefficient, and its value range is 1-2. When the weather has no effect on the vehicle's driving, the value of T is 2, and T is affected by the weather. The gross weight g represents the sum of the weight of the vehicle and the cargo; The blocking weight Q represents a value reflecting the traffic congestion situation, and the blocking weight Q is a dimensionless coefficient after normalization, and the value range of the blocking weight is 1-2. When the blocking weight is 1, it means that there is no congestion on the road ahead, and Q increases with the impact of the congestion ahead; When 3×10 4 <J<9×10 4 When , it means that the dispatch management module determines that the road ahead is seriously congested or the weather has a great impact on vehicle driving, or both, and then selects an alternative route; When 9×10 4 ≤J<<1.×10 5 When , it means that the congestion ahead is light or there is no congestion and the weather has little impact on vehicle driving, thereby guiding the vehicle to continue moving forward.

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