A comprehensive management and monitoring system for fuel cell forklifts based on smart Internet of Things

Abstract

The present application relates to a comprehensive management and monitoring system for fuel cell forklifts based on the intelligent Internet of Things, including a vehicle-mounted data acquisition terminal that collects real-time status information of fuel cell forklifts and transmits it to a cloud platform; the intelligent decision-making module of the cloud platform estimates the fuel usage of each monitoring area based on the collection results of the vehicle-mounted data acquisition terminal, generates a fuel supply plan and sends it to the data management terminal of the fuel supply center, and the intelligent decision-making module also evaluates the battery health of the forklift based on the collection results, issues an early warning when a battery abnormality is detected, and generates a fault repair plan and sends it to the maintenance dispatch center; the maintenance dispatch center determines the location of the faulty vehicle and dispatches maintenance personnel to the site for repair. The system can centrally and remotely manage the use of fuel cell forklifts in multiple monitoring areas, reduce labor input, and improve management efficiency and level.

Description

Technical Field

[0001] The present application relates to the technical field of fuel cell forklifts, and in particular to a comprehensive management and monitoring system for fuel cell forklifts based on a smart Internet of Things. Background Art

[0002] At present, when performing loading and unloading tasks, fuel cell forklifts need to monitor and manually record the working status of hydrogen fuel cells on site, and then analyze and solve problems. It is difficult to detect various working data of hydrogen fuel cells in real time. Fuel cell forklifts require users to actively understand the remaining fuel of fuel cell electric vehicles, and they also need to conduct periodic manual inspections of forklifts. The workload is large. When forklifts are distributed in different areas and there are many of them, it is even more difficult to centrally manage and uniformly deploy them. Therefore, it is necessary to develop relevant management service systems to solve these problems. Summary of the invention

[0003] In order to solve the technical problems mentioned in the above background technology or at least partially solve the above technical problems, the present application provides a comprehensive management and monitoring system for fuel cell forklifts based on the smart Internet of Things to reduce labor input and improve management efficiency and level.

[0004] The present application provides a comprehensive management and monitoring system for fuel cell forklifts based on the smart Internet of Things, including: an on-board data acquisition terminal, a cloud platform, a fuel supply station, and a maintenance dispatch center;

[0005] The vehicle-mounted data acquisition terminal is used to collect real-time status information of the fuel cell forklift and transmit it to the cloud platform; multiple fuel cell forklifts are distributed in multiple monitoring areas;

[0006] The cloud platform is provided with an intelligent decision-making module, which is used to estimate the fuel usage of each of the monitoring areas according to the collection results of the vehicle-mounted data collection terminal, generate a fuel supply plan according to the estimated results and send it to the data management terminal provided at the fuel supply station, so that the data management terminal dispatches a mobile hydrogen refueling vehicle to deliver hydrogen to each monitoring area;

[0007] The intelligent decision-making module is also used to evaluate the battery health of each forklift according to the collection results of the vehicle-mounted data collection terminal, issue an early warning when a battery abnormality is detected, and generate a fault repair plan and send it to the maintenance dispatch center;

[0008] The maintenance dispatch center determines the location of the faulty vehicle through a positioning system and dispatches maintenance personnel to the site for timely maintenance.

[0009] Optionally, it also includes a programmable controller PLC, a LoRa radio station and a LoRa base station;

[0010] Each monitoring area is equipped with the programmable controller PLC and the LoRa radio station. Multiple vehicle-mounted data acquisition terminals in the same monitoring area form a grid network and are respectively connected to the programmable controller PLC; the programmable controller PLC is connected to the regional LoRa radio station, the LoRa radio station is connected to the LoRa base station, and the LoRa base station is connected to the cloud platform.

[0011] Optionally, the real-time status information includes the battery temperature, battery hydrogen parameters, battery air parameters and current value of the fuel cell at the current moment, fuel usage, forklift loading information, forklift driving speed information, forklift location information, driver status information and remaining fuel amount.

[0012] Optionally, the intelligent decision-making module is used to estimate the fuel usage of each monitoring area according to the collection results of the vehicle-mounted data collection terminal, generate a fuel supply plan according to the estimated results and send it to the data management terminal provided at the fuel supply station, specifically including:

[0013] The fuel usage of forklifts in each monitoring area is accumulated to obtain fuel consumption data;

[0014] Obtaining the historical total cargo volume and the remaining inventory in the monitoring area, and obtaining an estimated fuel consumption amount based on the historical total cargo volume and the cargo inventory;

[0015] The mobile hydrogen refueling vehicle that needs to be dispatched is determined based on the estimated fuel consumption to obtain a fuel supply plan.

[0016] Optionally, the intelligent decision-making module is further used to evaluate the battery health of each forklift according to the collection results of the vehicle-mounted data collection terminal, specifically including:

[0017] The ideal open-circuit electromotive force at the current moment is calculated based on the current fuel cell stack temperature, hydrogen stack pressure, and oxygen stack pressure. The formula is as follows:

[0018]

[0019] Among them, E k represents the ideal open circuit electromotive force, T represents the battery stack temperature, P H2 Indicates the pressure inside the hydrogen stack, P O2 represents the oxygen pile internal pressure, k represents the acquisition time;

[0020] The concentration loss electromotive force and polarization loss electromotive force are calculated according to the real-time current value, real-time voltage value and ideal open circuit electromotive force of the fuel cell at the current moment. The calculation formula is:

[0021]

[0022] U s，k =E k -U 1，k-1 -U 2，k-1 -R 0，k ×I k

[0023] Among them, U s，k is the real-time voltage value across the fuel cell, I k is the real-time current value of the fuel cell, R 0，k is the theoretical DC internal resistance of the fuel cell at the current moment, A and B represent the set parameter matrices, where the A matrix expression is:

[0024]

[0025] The B matrix expression is:

[0026]

[0027] Wherein, ΔT is the sampling time interval, R1 is the resistance component of the activation internal resistance of the fuel cell, C1 is the capacitance component of the activation internal resistance of the fuel cell, R2 is the resistance component of the concentration difference internal resistance of the fuel cell, and C2 is the capacitance component of the concentration difference internal resistance;

[0028] The real-time DC internal resistance of the fuel cell at the current moment is calculated based on the concentration loss electromotive force and polarization loss electromotive force. The calculation formula is:

[0029]

[0030] According to the following calculation formula:

[0031]

[0032] Calculate the health index W of the fuel cell, where R s，k is the real-time DC internal resistance of the fuel cell, R 0，0 is the initial internal resistance of the fuel cell, R N，N is the final internal resistance of the fuel cell.

[0033] Optionally, the mobile terminal is connected to the cloud platform, and the cloud platform is also used to send the fault repair plan to the mobile terminal of the maintenance personnel.

[0034] Optionally, the positioning system includes a UWB positioning tag arranged on each fuel cell forklift and a UWB base station arranged in each monitoring area.

[0035] The above-mentioned technical solution provided by the embodiment of the present application has the following advantages compared with the prior art: the system collects the real-time fuel status information of each forklift in each monitoring area in real time through the on-board data acquisition terminal (such as the battery temperature, battery hydrogen parameters, battery air parameters and current value of the fuel cell at the current moment, fuel usage, forklift loading information, forklift driving speed information, forklift location information, driver status information and remaining fuel amount), and connects to the cloud platform through the LoRa radio and the LoRa base station. The intelligent decision-making module of the cloud platform can grasp the operation status of the forklift in each monitoring area in real time according to the collection results of multiple on-board data acquisition terminals, and then generate a fuel supply plan and a fault repair plan according to the operation status. The data management terminal of the fuel supply center can communicate with the cloud platform to realize the intelligent automation and precision of fuel supply, so that the management personnel can remotely manage the use of fuel cell forklifts in multiple monitoring areas through the data management terminal, reduce labor input, and improve management efficiency and level.

[0036] On the other hand, the various monitoring areas of the system are interconnected by setting up LoRa radio stations and LoRa base station networks. The network has good scalability and can monitor a wide area. When a forklift failure is detected, maintenance personnel can be dispatched to the site for repair in a timely manner, which is convenient and quick. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0039] Figure 1 A schematic diagram of the structure of a comprehensive management and monitoring system for fuel cell forklifts based on the smart Internet of Things provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0041] For ease of understanding, the following is a detailed description of a fuel cell forklift integrated management and monitoring system based on the smart Internet of Things provided in an embodiment of the present application, see Figure 1 , the present application provides a comprehensive management and monitoring system for fuel cell forklifts based on the smart Internet of Things, including: an on-board data acquisition terminal, a cloud platform, a fuel supply station, and a maintenance dispatch center;

[0042] The vehicle-mounted data acquisition terminal is used to collect real-time status information of the fuel cell forklift and transmit it to the cloud platform; multiple fuel cell forklifts are distributed in multiple monitoring areas;

[0043] The cloud platform is provided with an intelligent decision-making module, which is used to estimate the fuel usage of each of the monitoring areas according to the collection results of the vehicle-mounted data collection terminal, generate a fuel supply plan according to the estimated results and send it to the data management terminal provided at the fuel supply station, so that the data management terminal dispatches a mobile hydrogen refueling vehicle to deliver hydrogen to each monitoring area;

[0044] The intelligent decision-making module is also used to evaluate the battery health of each forklift according to the collection results of the vehicle-mounted data collection terminal, issue an early warning when a battery abnormality is detected, and generate a fault repair plan and send it to the maintenance dispatch center;

[0045] The maintenance dispatch center determines the location of the faulty vehicle through a positioning system and dispatches maintenance personnel to the site for timely maintenance.

[0046] Each monitoring area is equivalent to a forklift working area, and the various monitoring areas can be distributed and set in different locations. In some specific embodiments of the present application, the on-board data acquisition terminal can refer to a device or product used to collect forklift information. The real-time status information includes the battery temperature of the fuel cell at the current moment, the battery hydrogen parameters, the battery air parameters and the current value, fuel usage, forklift loading information, forklift driving speed information, forklift location information, driver status information, and remaining fuel.

[0047] As an example, the on-board data acquisition terminal can collect whether the forklift is working online (i.e., the forklift's working status information), the forklift's cargo weight and the fork status of the forklift (i.e., the forklift's cargo status), the forklift's driving speed data, the forklift's real-time location, the identity information of the driver driving the forklift, vital signs information (i.e., driver status information, such as blood pressure and body temperature), fuel usage, remaining fuel, battery temperature at the time of collection, battery hydrogen parameters (i.e., pressure inside the hydrogen stack), battery air parameters (pressure inside the oxygen stack), and hydrogen concentration in the air outside the hydrogen storage tank of the fuel cell forklift (i.e., monitoring whether hydrogen is leaking); the on-board data acquisition terminal transmits the collection results to the cloud platform through the communication module, and the cloud platform is equipped with an intelligent decision-making module.

[0048] In some specific embodiments of the present application, the intelligent decision-making module is used to estimate the fuel usage of each monitoring area according to the collection results of the vehicle-mounted data collection terminal, generate a fuel supply plan according to the estimated results and send it to the data management terminal provided at the fuel supply station, specifically including:

[0049] The fuel usage of forklifts in each monitoring area is accumulated to obtain fuel consumption data;

[0050] Obtaining the historical total cargo volume and the remaining inventory in the monitoring area, and obtaining an estimated fuel consumption amount based on the historical total cargo volume and the cargo inventory;

[0051] The mobile hydrogen refueling vehicle that needs to be dispatched is determined based on the estimated fuel consumption to obtain a fuel supply plan.

[0052] The total fuel consumption (i.e., fuel consumption data) of all online forklifts in each monitoring area within a period of time is collected. The difference between the total historical cargo volume and the remaining inventory is the cargo loading and unloading volume completed by the forklift during this period. The fuel consumption data is divided by the cargo loading and unloading volume and multiplied by the cargo inventory to obtain the estimated fuel consumption; the estimated fuel consumption is divided by the fuel loading capacity of each mobile hydrogenation vehicle to obtain the number of mobile hydrogenation vehicles that need to be dispatched, and a fuel supply plan is generated. In some specific embodiments of the present application, the mobile hydrogenation vehicle is used to refuel the forklift.

[0053] As an example, the data management terminal can also include a loading and unloading operation module, which is used for the outside world to input the type and weight of the goods to be loaded and unloaded in each monitoring area (called loading and unloading operations) and send it to the intelligent decision-making module. The intelligent decision-making module automatically generates a fuel supply plan based on the above-mentioned loading and unloading operations, the number of forklifts working online, the fuel usage of the forklift's fuel cell, the remaining fuel, and the gas pressure information of the hydrogen storage tank.

[0054] In some embodiments of the present application, the intelligent decision-making module is further used to evaluate the battery health of each forklift according to the collection results of the vehicle-mounted data collection terminal, issue an early warning when a battery abnormality is detected, and generate a fault repair plan to send to the maintenance dispatch center. Evaluating the battery health of each forklift includes the following steps:

[0055] The ideal open-circuit electromotive force at the current moment is calculated based on the current fuel cell stack temperature, hydrogen stack pressure, and oxygen stack pressure. The formula is as follows:

[0056]

[0057] Where E represents the ideal open circuit electromotive force, T represents the battery stack temperature, P H2Indicates the pressure inside the hydrogen stack, P O2 represents the oxygen pile internal pressure, k represents the acquisition time;

[0058] The concentration loss electromotive force and polarization loss electromotive force are calculated according to the real-time current value, real-time voltage value and ideal open circuit electromotive force of the fuel cell at the current moment. The calculation formula is:

[0059]

[0060] U s，k =E k -U 1，k-1 -U 2，k-1 -R 0，k ×I k

[0061] Among them, U s，k is the real-time voltage value across the fuel cell, I k is the real-time current value of the fuel cell, R 0，k is the theoretical DC internal resistance of the fuel cell at the current moment, A and B represent the set parameter matrices, where the A matrix expression is:

[0062]

[0063] The B matrix expression is:

[0064]

[0065] Wherein, ΔT is the sampling time interval, R1 is the resistance component of the activation internal resistance of the fuel cell, C1 is the capacitance component of the activation internal resistance of the fuel cell, R2 is the resistance component of the concentration difference internal resistance of the fuel cell, and C2 is the capacitance component of the concentration difference internal resistance;

[0066] The real-time DC internal resistance of the fuel cell at the current moment is calculated based on the concentration loss electromotive force and polarization loss electromotive force. The calculation formula is:

[0067]

[0068] According to the following calculation formula:

[0069]

[0070] Calculate the health index W of the fuel cell, where R s，k is the real-time DC internal resistance of the fuel cell, R 0，0 is the initial internal resistance of the fuel cell, R N，N is the final internal resistance of the fuel cell.

[0071] The theoretical DC internal resistance, the resistance component of the activation internal resistance, the capacitance component of the activation internal resistance, the resistance component of the concentration difference internal resistance and the capacitance component of the concentration difference internal resistance of the fuel cell at the current discrete operation time are obtained through the existing durability test and impedance analyzer, and the second-order model of the fuel cell is established to obtain the A matrix and the B matrix. After the second-order model is established, the initial internal resistance of the fuel cell and the final internal resistance of the fuel cell can also be obtained.

[0072] As time goes by and the internal state changes, the internal resistance of the fuel cell will continue to increase and change during operation. The size of the internal resistance directly reflects the health status of the battery to a certain extent.

[0073] In some specific embodiments of the present application, a programmable controller PLC, a LoRa radio station and a LoRa base station are also included;

[0074] Each monitoring area is equipped with the programmable controller PLC and the LoRa radio station. Multiple vehicle-mounted data acquisition terminals in the same monitoring area form a grid network and are respectively connected to the programmable controller PLC; the programmable controller PLC is connected to the regional LoRa radio station, the LoRa radio station is connected to the LoRa base station, and the LoRa base station is connected to the cloud platform.

[0075] Each monitoring area is equipped with a programmable controller PLC and a LoRa radio station. Multiple vehicle-mounted data acquisition terminals in the same monitoring area form a grid network and are each connected to the programmable controller PLC; the programmable controller PLC is connected to the regional LoRa radio station, the LoRa radio station is connected to the LoRa base station, and the LoRa base station is connected to the cloud platform.

[0076] In some specific embodiments of the present application, the vehicle-mounted data acquisition terminals of different forklifts in the same monitoring area can form a grid network. When the data collected by a certain vehicle-mounted data acquisition terminal cannot be directly uploaded to the corresponding programmable controller PLC, the detection data can be uploaded through other vehicle-mounted data acquisition terminals that are interconnected with it, thereby avoiding data loss and improving the reliability of data acquisition. The data collected by the vehicle-mounted data acquisition terminal is transmitted to the programmable controller PLC, and the programmable controller PLC can process the collected data (for example, the coding identifier of the programmable controller PLC and the collected data are packaged to generate a one-to-one correspondence, where each programmable controller PLC corresponds to a unique coding identifier) ​​and then finally transmitted to the cloud platform through the LoRa radio station via the LoRa base station.

[0077] To facilitate maintenance, in some specific embodiments of the present application, the mobile terminal is connected to the cloud platform, and the cloud platform is also used to send the fault repair plan to the mobile terminal of the maintenance personnel.

[0078] In some specific embodiments of the present application, the positioning system includes a UWB positioning tag provided on each fuel cell forklift and a UWB base station provided in each monitoring area.

[0079] Each monitoring area is equipped with at least four UWB base stations, and the UWB base stations and UWB tags are adapted to achieve real-time positioning of forklifts.

[0080] The system collects the real-time fuel status information of each forklift in each monitoring area through the on-board data acquisition terminal (such as forklift working status information, forklift loading status information, forklift driving speed information, forklift location information, driver status information, fuel cell remaining power information, fuel cell temperature and humidity information, fuel cell voltage information and hydrogen leakage information), and connects to the cloud platform through the LoRa radio and LoRa base station. The intelligent decision-making module of the cloud platform can grasp the operation status of the forklift in each monitoring area in real time according to the collection results of multiple on-board data acquisition terminals, and then generate fuel supply plans and fault repair plans according to the operation status. The data management terminal of the fuel supply center can communicate with the cloud platform to realize the intelligent automation and precision of fuel supply, so that managers can remotely manage the use of fuel cell forklifts in multiple monitoring areas through the data management terminal, reduce labor input, and improve management efficiency and level.

[0081] On the other hand, the various monitoring areas of the system are interconnected by setting up LoRa radio stations and LoRa base station networks. The network has good scalability and can monitor a wide area. When a forklift failure is detected, maintenance personnel can be dispatched to the site for repair in a timely manner, which is convenient and quick.

[0082] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0083] The foregoing is merely a specific embodiment of the present invention, which enables those skilled in the art to understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A comprehensive management and monitoring system for fuel cell forklifts based on the intelligent Internet of Things, characterized in that: include: On-board data collection terminal, cloud platform, fuel supply terminal and maintenance dispatch center; The vehicle-mounted data acquisition terminal is used to collect real-time status information of the fuel cell forklift and transmit it to the cloud platform; multiple fuel cell forklifts are distributed in multiple monitoring areas; The cloud platform is provided with an intelligent decision-making module, which is used to estimate the fuel usage of each of the monitoring areas according to the collection results of the vehicle-mounted data collection terminal, generate a fuel supply plan according to the estimated results and send it to the data management terminal provided at the fuel supply station, so that the data management terminal dispatches a mobile hydrogen refueling vehicle to deliver hydrogen to each monitoring area; The intelligent decision-making module is also used to evaluate the battery health of each forklift according to the collection results of the vehicle-mounted data collection terminal, issue an early warning when a battery abnormality is detected, and generate a fault repair plan and send it to the maintenance dispatch center; The maintenance dispatch center determines the location of the faulty vehicle through the positioning system and dispatches maintenance personnel to the site for timely maintenance; The intelligent decision-making module is also used to evaluate the battery health of each forklift according to the collection results of the vehicle-mounted data collection terminal, specifically including: The ideal open-circuit electromotive force at the current moment is calculated based on the current fuel cell stack temperature, hydrogen stack pressure, and oxygen stack pressure. The formula is as follows: Among them, E k represents the ideal open circuit electromotive force, T represents the battery stack temperature, P H2 Indicates the pressure inside the hydrogen stack, P O2 represents the oxygen pile internal pressure, k represents the acquisition time; The concentration loss electromotive force and polarization loss electromotive force are calculated according to the real-time current value, real-time voltage value and ideal open circuit electromotive force of the fuel cell at the current moment. The calculation formula is: U s,k =E k -U1,k-1-U2,k-1-R0,k×I k Among them, U s,k is the real-time voltage value across the fuel cell, I k is the real-time current value of the fuel cell, R 0,k The theoretical DC internal resistance B of the fuel pool at the current moment represents the set parameter matrix, where the B matrix expression is: Where ΔT is the sampling time interval, C1 is the capacitance component of the activation internal resistance of the fuel cell, and C2 is the capacitance component of the concentration difference internal resistance; The real-time DC internal resistance of the fuel cell at the current moment is calculated based on the concentration loss electromotive force and polarization loss electromotive force. The calculation formula is: According to the following calculation formula: Calculate the health index W, R of the fuel cell s,k is the real-time DC internal resistance of the fuel cell, R 0,0 is the initial internal resistance of the fuel cell, R N,N is the final internal resistance of the fuel cell.

2. According to claim 1, a fuel cell forklift integrated management and monitoring system based on the intelligent Internet of Things is characterized in that: It also includes a programmable controller PLC, a LoRa radio station and a LoRa base station; Each monitoring area is equipped with the programmable controller PLC and the LoRa radio station. Multiple vehicle-mounted data acquisition terminals in the same monitoring area form a grid network and are respectively connected to the programmable controller PLC; the programmable controller PLC is connected to the regional LoRa radio station, the LoRa radio station is connected to the LoRa base station, and the LoRa base station is connected to the cloud platform.

3. According to claim 2, a fuel cell forklift integrated management and monitoring system based on the intelligent Internet of Things is characterized in that: The real-time status information includes the current battery temperature, battery hydrogen parameters, battery air parameters and current value of the fuel cell, fuel usage, forklift loading information, forklift driving speed information, forklift location information, driver status information and remaining fuel.

4. According to claim 3, a fuel cell forklift integrated management and monitoring system based on the intelligent Internet of Things is characterized in that: The intelligent decision-making module is used to estimate the fuel usage of each monitoring area according to the collection results of the vehicle-mounted data collection terminal, generate a fuel supply plan according to the estimated results and send it to the data management terminal provided at the fuel supply station, specifically including: The fuel usage of forklifts in each monitoring area is accumulated to obtain fuel consumption data; Obtain the total historical cargo volume and remaining inventory in the monitoring area. The difference between the total historical cargo volume and the remaining inventory is the cargo loading and unloading volume completed by the forklift during this period. The fuel consumption data is divided by the cargo loading and unloading volume and multiplied by the cargo inventory to obtain the estimated fuel consumption. The mobile hydrogen refueling vehicle that needs to be dispatched is determined based on the estimated fuel consumption to obtain a fuel supply plan.

5. According to claim 3, a fuel cell forklift integrated management and monitoring system based on the intelligent Internet of Things is characterized in that: The mobile terminal is connected to the cloud platform, and the cloud platform is also used to send the fault repair plan to the mobile terminal of the maintenance personnel.

6. A fuel cell forklift integrated management and monitoring system based on the intelligent Internet of Things according to any one of claims 1 to 5, characterized in that: The positioning system includes a UWB positioning tag arranged on each fuel cell forklift and a UWB base station arranged in each monitoring area.

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