CN113085592B - Method and system for predicting driving range of hydrogen fuel cell dump truck in real time - Google Patents
Method and system for predicting driving range of hydrogen fuel cell dump truck in real time Download PDFInfo
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- 239000000446 fuel Substances 0.000 title claims abstract description 97
- 239000001257 hydrogen Substances 0.000 title claims abstract description 81
- 229910052739 hydrogen Inorganic materials 0.000 title claims abstract description 81
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 title claims abstract description 79
- 238000000034 method Methods 0.000 title claims abstract description 45
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- 238000004891 communication Methods 0.000 claims description 7
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L50/00—Electric propulsion with power supplied within the vehicle
- B60L50/50—Electric propulsion with power supplied within the vehicle using propulsion power supplied by batteries or fuel cells
- B60L50/75—Electric propulsion with power supplied within the vehicle using propulsion power supplied by batteries or fuel cells using propulsion power supplied by both fuel cells and batteries
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L58/00—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles
- B60L58/40—Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for controlling a combination of batteries and fuel cells
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
- Y02T90/40—Application of hydrogen technology to transportation, e.g. using fuel cells
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- Life Sciences & Earth Sciences (AREA)
- Sustainable Development (AREA)
- Sustainable Energy (AREA)
- Power Engineering (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Fuel Cell (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
The invention relates to the technical field of driving range calculation, in particular to a method and a system for predicting the driving range of a hydrogen fuel cell dumper in real time, wherein the method comprises the following steps: s1, acquiring data related to a power battery pack of a hydrogen fuel cell dumper and residual data of a fuel cell; s2, detecting whether the acquired data is complete, if so, executing a step S3, otherwise, executing a step S4; s3, identifying the missing data, calling historical data of the missing data to supplement, and then executing the step S4; s4, constructing a driving range prediction model; s5, carrying out regression analysis on the acquired data through a range prediction model to obtain a current range prediction value of the dump truck. According to the invention, the driving mileage of the hydrogen fuel cell dumper is predicted by monitoring various factors influencing the driving mileage of the dumper in real time, so that the prediction accuracy is improved, and the dumper can be timely supplemented with energy when the dumper is insufficient in energy, thereby prolonging the service life of the dumper and relieving the mileage anxiety phenomenon.
Description
Technical Field
The invention relates to the technical field of driving range calculation, in particular to a method and a system for predicting the driving range of a hydrogen fuel cell dumper in real time.
Background
The hydrogen fuel cell dumper takes a fuel cell as a main energy source and a power battery pack as an auxiliary energy source to provide power for the dumper, and has the characteristics of zero pollution, high energy conversion efficiency, low noise and the like. Because the dump truck has bad driving condition and large carrying capacity, the driving mileage of the dump truck is difficult to control by a driver. In the past, the driver combined hundred kilometers of energy consumption and residual electric quantity of the hydrogen fuel cell dumper approximately estimates the driving range of the vehicle, but the dumper has larger error of estimation results due to the variability of driving behaviors, terrains and other influencing factors of the driver and larger weight in the actual working process, and the driving range of the hydrogen fuel cell dumper cannot be accurately predicted in real time.
The Chinese patent document with publication number of CN112389213A discloses a driving range prediction method, device, equipment and storage medium, by the technical scheme, the driving capability of a fuel cell and the driving capability of a power cell can be integrated, the influence of environmental factors such as weather conditions, road traffic conditions and the like is considered, the driving range of a vehicle is accurately predicted, and the problem of mileage anxiety of a driver is relieved.
However, in the above scheme, if a vehicle has a local fault, the driving range cannot be predicted, so that the application range of the prediction method is smaller.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a method and a system for predicting the driving range of a hydrogen fuel cell dumper in real time.
In order to solve the technical problems, the invention adopts the following technical scheme:
the method for predicting the driving range of the hydrogen fuel cell dumper in real time comprises the following steps:
s1, acquiring data related to a power battery pack of a hydrogen fuel cell dumper and residual data of a fuel cell;
s2, detecting whether the data acquired in the step S1 are complete, if yes, executing the step S4, otherwise, executing the step S3;
s3, identifying missing data, calling historical data of the missing data to supplement, and then executing step S4;
s4, constructing a driving range prediction model;
s5, carrying out regression analysis on the acquired data through the range prediction model after the step S4 to obtain a current range prediction value of the dump truck.
The invention comprises a method for predicting the driving range of the hydrogen fuel cell dumper in real time, wherein various factors influencing the driving range of the hydrogen fuel cell dumper, such as data related to a power battery pack and data of the residual quantity of a fuel cell, can be used for predicting the driving range of the dumper more accurately, and are used for prompting a driver to supplement energy in time, so that the service life of a power supply system is prolonged, and the problem of mileage anxiety is relieved. In addition, the prediction method can also confirm whether the dump truck has a local fault by detecting corresponding missing data, and can still predict the driving range in real time when the dump truck has the local fault.
Further, the method further comprises the step S6: after step S5, the data acquired in step S1 is added to the history data, and then step S1 is returned.
Further, in step S1, the power battery pack related data includes a power battery pack total capacitance, a power battery pack residual change rate, a power battery pack discharging depth, a power battery pack temperature, a power battery pack charging and discharging total voltage, a power battery pack charging and discharging total current, a power battery pack output power, a power battery pack single battery voltage, and a power battery pack single battery discharging depth.
Further, the method further comprises the step S7: after step S1, coordinating the energy supply relationship between the power battery pack and the fuel cell by the power battery pack margin; wherein, the step S7 body comprises:
s71, setting the residual quantity of the current power battery pack to be A SOC Let the maximum safety value of the power battery pack allowance be A max Setting the minimum safety value A of the power battery pack allowance min The method comprises the steps of carrying out a first treatment on the surface of the When A is SOC ≥A max At this time, step S62 is performed; when A is SOC ≤A min At this time, step S63 is performed; when A is min <A SOC <A max At this time, step S64 is performed;
s72, adjusting the output power of the fuel cell to enable the output power of the fuel cell to be lower than the load demand power of a driving motor of the dump truck;
s73, adjusting the output power of the fuel cell to enable the fuel cell to work at the maximum output power;
s74, adjusting the output power of the fuel cell according to the load demand power of the driving motor of the dump truck, enabling the power battery pack and the fuel cell to work simultaneously, and enabling the A to be SOC ∈[A 1 ,A 2 ]The method comprises the steps of carrying out a first treatment on the surface of the Wherein [ A ] 1 ,A 2 ]The remaining capacity of the power battery pack in a healthy state is indicated.
Further, in step S1, the method further includes acquiring vehicle body environment data and vehicle exterior environment data of the hydrogen fuel cell dump truck.
Further, the vehicle exterior environment data includes travel gradient data; the vehicle body environment data comprise vehicle body temperature data, vehicle body pressure data, vehicle body speed data and hydrogen storage tank data.
Further, in step S1, the fuel cell residual data is calculated by the gas pressure of the gas tank and the modified gas state equation; wherein, the gas storage tank air pressure and the correction gas state equation are:
wherein X is Burning Representing the current fuel cell allowance of the dump truck, P represents the pressure in a hydrogen storage tank acquired in real time, and P 0 Pressure of the hydrogen storage tank indicating that the fuel cell reaches the minimum hydrogen consumption, V indicates the volume of the hydrogen storage tank, and Z c Represents the gas compression factor, R represents the ideal gas constant, T represents the gas Kelvin temperature, eta 1 Represents the hydrogen utilization rate, eta of the dump truck 2 Represents the hydrogen conversion rate, eta 3 Representing the power output efficiency.
Further, in step S4, the driving range prediction model is:
wherein L is Pre-preparation X represents the predicted value of the current driving range of the dump truck i Representing influence factors of driving range of dump truck, k i Representing the fitting parameters.
The invention also provides a real-time prediction system for the driving range of the hydrogen fuel cell dumper, which comprises the following steps: the system comprises a sensing system, a battery monitoring system, a data transmission processing system and a network computing system, wherein the sensing system, the battery monitoring system and the network computing system are all in communication connection with the data transmission processing system.
The invention also comprises a real-time prediction system for the driving mileage of the hydrogen fuel cell dumper, wherein the sensing system is used for acquiring the environmental data of the dumper body and the external environmental data of the dumper body in the running process of the hydrogen fuel cell dumper; the battery monitoring system is used for acquiring related data of the power battery pack in the running process of the hydrogen fuel cell dumper; the data transmission processing system is used for preprocessing, classifying and storing various data acquired by the sensing system and the battery monitoring system and transmitting the data; the network computing system is used for predicting the data transmitted by the data transmission processing system to obtain the current driving range predicted value of the dump truck.
Preferably, the sensing system comprises a temperature sensing module, a pressure sensing module, a gas pressure sensing module, a speed sensing module and a gradient sensing module which are in communication connection with the data transmission processing system.
Compared with the prior art, the invention has the beneficial effects that:
the invention comprises a method for predicting the driving range of the hydrogen fuel cell dumper in real time, wherein various factors influencing the driving range of the hydrogen fuel cell dumper, such as data related to a power battery pack and data of the residual quantity of a fuel cell, can be used for predicting the driving range of the dumper more accurately, and are used for prompting a driver to supplement energy in time, so that the service life of a power supply system is prolonged, and the problem of mileage anxiety is relieved. In addition, the prediction method can also confirm whether the dump truck has a local fault by detecting corresponding missing data, and can still predict the driving range in real time when the dump truck has the local fault.
The invention also comprises a real-time prediction system for the driving mileage of the hydrogen fuel cell dumper, wherein the sensing system is used for acquiring the environmental data of the dumper body and the external environmental data of the dumper body in the running process of the hydrogen fuel cell dumper; the battery monitoring system is used for acquiring related data of the power battery pack in the running process of the hydrogen fuel cell dumper; the data transmission processing system is used for preprocessing various data acquired by the sensing system and the battery monitoring system and transmitting the data; the network computing system is used for predicting the data transmitted by the data transmission processing system to obtain the current driving range predicted value of the dump truck.
Drawings
Fig. 1 is a flowchart of an embodiment 1 of a method for predicting the driving range of a hydrogen fuel cell dump truck in real time.
Fig. 2 is a flowchart of an embodiment 2 of a method for predicting the driving range of a hydrogen fuel cell dump truck in real time.
Fig. 3 is a flowchart of an embodiment 3 of a method for predicting the driving range of a hydrogen fuel cell dump truck in real time.
Fig. 4 is a schematic connection diagram of a real-time prediction system for the driving range of a hydrogen fuel cell dump truck.
Detailed Description
The invention is further described below in connection with the following detailed description. Wherein the drawings are for illustrative purposes only and are shown in schematic, non-physical, and not intended to be limiting of the present patent; for the purpose of better illustrating embodiments of the invention, certain elements of the drawings may be omitted, enlarged or reduced and do not represent the size of the actual product; it will be appreciated by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted.
The same or similar reference numbers in the drawings of embodiments of the invention correspond to the same or similar components; in the description of the present invention, it should be understood that, if there is an azimuth or positional relationship indicated by terms such as "upper", "lower", "left", "right", etc., based on the azimuth or positional relationship shown in the drawings, it is only for convenience of describing the present invention and simplifying the description, but it is not indicated or implied that the apparatus or element referred to must have a specific azimuth, be constructed and operated in a specific azimuth, and thus terms describing the positional relationship in the drawings are merely illustrative and should not be construed as limitations of the present patent, and specific meanings of the terms described above may be understood by those skilled in the art according to specific circumstances.
Example 1
Fig. 1 shows a first embodiment of a method for predicting the driving range of a hydrogen fuel cell dump truck in real time, which comprises the following steps:
s1, acquiring power battery pack related data, vehicle body environment data and vehicle exterior environment data of the hydrogen fuel cell dumper through a sensing system, and acquiring fuel cell allowance data through calculation and analysis.
The power battery pack related data comprise total capacity of the power battery pack, residual power battery pack (SOC) change rate, depth of discharge of the power battery pack, temperature of the power battery pack, total charge and discharge voltage of the power battery pack, total charge and discharge current of the power battery pack, output power of the power battery pack, voltage of a single battery of the power battery pack and depth of discharge of the single battery of the power battery pack. The relevant data of the power battery pack are obtained in real time through a CAN bus, specifically, the relevant data of the power battery pack are transmitted to a battery monitoring system through the CAN bus, and then are transmitted to a data transmission processing system through the battery monitoring system.
The fuel cell residual data is calculated through the air pressure of the air storage tank and the state equation of the correction gas; wherein, the air pressure of the air storage tank and the state equation of the correction gas are as follows:
wherein X is Burning Representing the current fuel cell allowance of the dump truck, P represents the pressure in a hydrogen storage tank acquired in real time, and P 0 Pressure of the hydrogen storage tank indicating that the fuel cell reaches the minimum hydrogen consumption, V indicates the volume of the hydrogen storage tank, and Z c Represents the gas compression factor, R represents the ideal gas constant, T represents the gas Kelvin temperature, eta 1 Represents the hydrogen utilization rate, eta of the dump truck 2 Represents the hydrogen conversion rate, eta 3 Representing the power output efficiency. The pressure in the hydrogen storage tank which is acquired in real time and indicated by P can be acquired in real time through the air pressure sensor.
It should be noted that, some hydrogen is used for supplying energy to some electrical equipment mounted on the dump truck in the process of inputting the hydrogen into the fuel cell, so that the problem of high conversion rate exists when the chemical energy of the hydrogen is converted into electric energy by the fuel cell, after the electric energy is generated, only part of the electric energy is used for driving the dump truck of the hydrogen cell to travel, and therefore, the residual data of the hydrogen cell can be calculated through the air pressure of the air storage tank and the correction gas state equation.
The vehicle body environment data comprise vehicle body temperature data, vehicle body pressure data, vehicle body speed data and hydrogen storage tank data. The vehicle body temperature data is acquired through a temperature sensor, the vehicle body pressure data is acquired through a pressure sensor, the vehicle body speed data is acquired through a speed sensor, and the hydrogen storage tank data is acquired through a pressure sensor.
Specifically, the vehicle body temperature data includes a vehicle body external temperature, an air conditioning temperature; the outside temperature of the automobile body is obtained in real time by installing the temperature sensor outside the automobile body, and the air conditioner temperature is obtained in real time by installing the temperature sensor on the air conditioner evaporation box.
Specifically, the vehicle body pressure data includes a dump truck load, a running resistance, and a running acceleration resistance; the load, the running resistance and the running acceleration resistance of the dump truck are all obtained in real time through the pressure sensor;
specifically, the vehicle body speed data includes a dump truck travel speed and a travel acceleration; the running speed and the running acceleration of the dump truck are obtained in real time through a speed sensor.
Specifically, the hydrogen storage tank data comprises the air pressure in the hydrogen storage tank bottle and the residual quantity of the hydrogen storage tank; the air pressure in the hydrogen storage tank bottle and the residual quantity of the hydrogen storage tank are obtained in real time through an air pressure sensor.
Specifically, the vehicle exterior environment data includes travel gradient data; the driving gradient data is acquired in real time through a gradient sensor.
And the data acquired by each sensor are sent to a data transmission processing system according to a preset communication protocol. The data types acquired by the respective sensors may be increased or decreased according to actual conditions, and the data type selection is only preferable.
S2, data transmission processing receives the data sent by the sensing system and stores the data in a classified mode, then the data transmission processing system detects whether the data acquired in the step S1 are complete, if yes, the step S4 is executed, and otherwise, the step S3 is executed.
It should be noted that the integrity of the acquired data may be set according to the actual situation. The integrity of the data in this embodiment refers to the lack of data related to the power battery pack, the fuel cell margin data, the vehicle body environment data, and the vehicle exterior environment data of the hydrogen fuel cell dump truck.
S3, identifying the missing data through the data transmission processing system, calling recent historical data stored under the missing data classification in the data transmission processing system to supplement, uploading the recent historical data to the internet-connected computing system in real time, and then executing the step S4. The data transmission processing system can also find out the corresponding fault component according to the missing data and display the fault component on the vehicle-mounted display system, so as to prompt a driver to repair the fault component.
It should be noted that, the recent historical data refers to the data of the same day and the same time in the last week of the current time node as historical data, and the historical data and other data received in real time are uploaded to the internet-connected computing system together. However, the selected time node of the historical data is only preferable, and may be specifically selected and set according to the actual situation.
S4, constructing a driving range prediction model through an internet-connected computing system; the driving range prediction model is as follows:
wherein L is Pre-preparation X represents the predicted value of the current driving range of the dump truck i Representing influence factors of driving range of dump truck, k i Representing the fitting parameters.
S5, after the step S4, the network computing system receives data sent by the data transmission processing system in real time, substitutes the data into a driving range prediction model to perform fitting, obtains a current driving range predicted value of the dump truck, sends the predicted value to the data transmission processing system, and sends the data transmission processing system to the vehicle-mounted display system to display.
According to the invention, the driving mileage is predicted by comprehensively considering the influences of the power battery state, the fuel battery allowance, the dump truck load, the external environment temperature and other factors of the hydrogen fuel battery dump truck, and the driving mileage prediction model is used for prediction, so that the prediction precision and the fitting goodness are higher, and the driving mileage of the hydrogen fuel battery dump truck can be accurately predicted.
Example 2
The present embodiment is similar to embodiment 1, except that, as shown in fig. 2, the prediction method in the present embodiment further includes S6: after step S5, the data acquired in step S1 is added to the history data by the data transmission processing system classification, and then step S1 is returned.
Specifically, after each prediction is finished, the data transmission processing system adds various data acquired in real time into historical data, a new driving range prediction model is fitted after the data is updated, so that the model is updated in real time, the newly obtained model is used for predicting the driving range at the next moment, and the step S1 is returned after the prediction is finished.
Example 3
The present embodiment is similar to embodiment 2, except that, as shown in fig. 3, the prediction method in the present embodiment further includes step S7: after step S1, coordinating the energy supply relationship between the power battery pack and the fuel cell by the power battery pack margin; wherein, the step S7 body comprises:
s71, setting the residual quantity of the current power battery pack to be A SOC Let the maximum safety value of the power battery pack allowance be A max Setting the minimum safety value A of the power battery pack allowance min ；
When A is SOC ≥A max At this time, step S72 is performed: the output power of the fuel cell is adjusted to be lower than the load demand power of the driving motor of the dump truck;
when A is SOC ≤A min At this time, step S73 is performed: adjusting the output power of the fuel cell to enable the fuel cell to work at the maximum output power;
when A is min <A SOC <A max When step S74 is executed: the output power of the fuel cell is regulated according to the load demand power of the driving motor of the dump truck, so that the power battery pack and the fuel cell work simultaneously, and A is realized SOC ∈[A 1 ,A 2 ]The method comprises the steps of carrying out a first treatment on the surface of the Wherein [ A ] 1 ,A 2 ]The remaining capacity of the power battery pack in a healthy state is indicated.
The rotational speed torque sensor is used for acquiring rotational speed torque of the dumper driving motor, and further, load demand power of the dumper driving motor is obtained.
The step S7 and the steps S2 to S6 are not sequential, and the step S7 may be performed at any time in the steps S2 to S6.
Example 4
Fig. 4 shows a first embodiment of a real-time prediction system for driving range of a hydrogen fuel cell dump truck according to the present invention, including:
the sensing system is used for acquiring vehicle body environment data and vehicle exterior environment data in the operation process of the hydrogen fuel cell dumper;
the battery monitoring system is used for acquiring the related data of the power battery pack in the operation process of the hydrogen fuel cell dumper and is also used for coordinating the energy supply relation between the power battery pack and the fuel cell;
the data transmission processing system is used for preprocessing, classifying and storing various data acquired by the sensing system and the battery monitoring system and transmitting the data;
the network computing system is used for predicting the data transmitted by the data transmission processing system to obtain the current driving mileage predicted value of the dump truck;
the sensing system, the battery monitoring system and the network computing system are all in communication connection with the data transmission processing system.
The sensing system comprises a temperature sensing module, a pressure sensing module, a speed sensing module and a gradient sensing module which are in communication connection with the data transmission processing system. In this embodiment, the temperature sensing module is a temperature sensor, the pressure sensing module is a pressure sensor, the air pressure sensing module is an air pressure sensor, the speed sensing module is a speed sensor, and the gradient sensing module is a gradient sensor.
Wherein, when being used for coordinating the energy supply relation between the power battery pack and the fuel battery, the battery monitoring system is realized through monitoring and adjusting the power battery pack allowance (SOC): firstly, setting a maximum safety value and a minimum safety value of the power battery pack allowance;
when the power battery pack residual (SOC) is equal to or greater than the maximum safety value of the power battery pack residual, if the power battery pack is continuously charged, an overcharge phenomenon is caused, and the power battery pack is damaged; at the moment, the output power of the fuel cell is regulated by the cell monitoring system, so that the output power of the fuel cell is slightly lower than the load demand power of the driving motor of the dump truck; the power battery pack participates in energy supply and is used as auxiliary energy to drive the dump truck to run, and at the moment, the power battery pack is in a discharging state, so that the power battery pack can be prevented from being overcharged;
when the power battery pack residual (SOC) is equal to or smaller than the minimum safety value of the power battery pack residual, if the power battery pack continues to discharge, an overdischarge phenomenon is caused; at the moment, the output power of the fuel cell is improved through the cell monitoring system, so that the fuel cell works at the maximum output power, the power battery pack stops supplying power, and the fuel cell charges the power battery pack on the premise of ensuring the normal running of the dump truck, so that the power battery pack is prevented from being over-discharged, and the power battery pack is protected;
when the power battery pack allowance (SOC) is between the maximum safety value and the minimum safety value, the power requirement of the load of the driving motor of the actual dump truck is combined, so that the power battery pack and the fuel battery work simultaneously, and the charging and discharging of the power battery pack are performed simultaneously and are maintained near the current SOC value.
The maximum safety value and the minimum safety value of the power battery pack margin can be set according to actual conditions.
As shown in fig. 4, the prediction system further includes an in-vehicle display system for displaying various data, and the in-vehicle display system is communicatively connected to the data transmission processing system. In this embodiment, the vehicle-mounted display system is a vehicle-mounted display screen, and the vehicle-mounted display screen can be used for displaying a current driving range predicted value of the dump truck and can also be used for displaying a corresponding fault part name found according to missing data.
Example 5
The embodiment is similar to embodiment 4, except that the system in this embodiment further includes a positioning system communicatively connected to the data transmission processing system, where the positioning system can be used to obtain the current running road condition data of the dump truck, and then upload the data to the data transmission processing system.
It is to be understood that the above examples of the present invention are provided by way of illustration only and are not intended to limit the scope of the invention. Other variations or modifications of the above teachings will be apparent to those of ordinary skill in the art. It is not necessary here nor is it exhaustive of all embodiments. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the invention are desired to be protected by the following claims.
Claims (9)
1. A method for predicting the driving range of a hydrogen fuel cell dumper in real time is characterized by comprising the following steps:
s1, acquiring data related to a power battery pack of a hydrogen fuel cell dumper and residual data of a fuel cell; the fuel cell residual data is calculated through the air pressure of the air storage tank and a modified gas state equation; wherein, the gas storage tank air pressure and the correction gas state equation are:
wherein X is Burning Representing the current fuel cell allowance of the dump truck, P represents the pressure in a hydrogen storage tank acquired in real time, and P 0 Pressure of the hydrogen storage tank indicating that the fuel cell reaches the minimum hydrogen consumption, V indicates the volume of the hydrogen storage tank, and Z c Represents the gas compression factor, R represents the ideal gas constant, T represents the gas Kelvin temperature, eta 1 Represents the hydrogen utilization rate, eta of the dump truck 2 Represents the hydrogen conversion rate, eta 3 Representing the power output efficiency;
s2, detecting whether the data acquired in the step S1 are complete, if yes, executing the step S4, otherwise, executing the step S3;
s3, identifying missing data, calling historical data of the missing data to supplement, and then executing step S4;
s4, constructing a driving range prediction model;
s5, carrying out regression analysis on the acquired data through the range prediction model after the step S4 to obtain a current range prediction value of the dump truck.
2. The method for predicting the driving range of the hydrogen fuel cell dump truck in real time according to claim 1, further comprising the step of S6: after step S5, the data acquired in step S1 is added to the history data, and then step S1 is returned.
3. The method for predicting the driving range of the hydrogen fuel cell dump truck according to claim 1, wherein in step S1, the power battery pack related data includes a total power battery pack capacitance, a power battery pack residual amount change rate, a power battery pack depth of discharge, a power battery pack temperature, a total power battery pack charge and discharge voltage, a total power battery pack charge and discharge current, a power battery pack output power, a power battery pack single battery voltage, and a power battery pack single battery depth of discharge.
4. The method for predicting the driving range of the hydrogen fuel cell dump truck in real time according to claim 1, further comprising the step of S7: after step S1, coordinating the energy supply relationship between the power battery pack and the fuel cell by the power battery pack margin; wherein, the step S7 body comprises:
s71, setting the residual quantity of the current power battery pack to be A SOC Let the maximum safety value of the power battery pack allowance be A max Minimum safety of power battery pack allowanceValue A min The method comprises the steps of carrying out a first treatment on the surface of the When A is SOC ≥A max At this time, step S72 is performed; when A is Soc ≤A min At this time, step S73 is performed; when A is min <A SOC <A max At this time, step S74 is performed;
s72, adjusting the output power of the fuel cell to enable the output power of the fuel cell to be lower than the load demand power of a driving motor of the dump truck;
s73, adjusting the output power of the fuel cell to enable the fuel cell to work at the maximum output power;
s74, adjusting the output power of the fuel cell to enable the power battery pack and the fuel cell to work simultaneously, and enabling A to be SOC ∈[A 1 ,A 2 ]The method comprises the steps of carrying out a first treatment on the surface of the Wherein [ A ] 1 ,A 2 ]The remaining capacity of the power battery pack in a healthy state is indicated.
5. The method for predicting the range of a hydrogen fuel cell dump truck according to claim 1, further comprising acquiring vehicle body environment data and vehicle exterior environment data of the hydrogen fuel cell dump truck in step S1.
6. The method for predicting the range of a hydrogen fuel cell dump truck in real time according to claim 5, wherein the vehicle exterior environment data includes travel gradient data; the vehicle body environment data comprise vehicle body temperature data, vehicle body pressure data, vehicle body speed data and hydrogen storage tank data.
7. The method for predicting the range of the hydrogen fuel cell dump truck according to claim 1, wherein in step S4, the range prediction model is:
wherein L is Pre-preparation X represents the predicted value of the current driving range of the dump truck i The driving distance of the dump truck is expressed,k i representing the fitting parameters.
8. A prediction system applied to the method for predicting the driving range of the hydrogen fuel cell dump truck in real time according to any one of claims 1 to 7, characterized by comprising:
the sensing system is used for acquiring vehicle body environment data and vehicle exterior environment data in the operation process of the hydrogen fuel cell dumper;
the battery monitoring system is used for acquiring data related to the power battery pack in the running process of the hydrogen fuel cell dumper;
the data transmission processing system is used for preprocessing, classifying and storing various data acquired by the sensing system and the battery monitoring system and transmitting the data;
the network computing system is used for predicting the data transmitted by the data transmission processing system to obtain the current driving range predicted value of the dump truck;
the sensing system, the battery monitoring system and the network computing system are all in communication connection with the data transmission processing system.
9. The predictive system of claim 8, wherein the sensing system includes a temperature sensing module, a pressure sensing module, a barometric pressure sensing module, a speed sensing module, a grade sensing module in communication with the data transmission processing system.
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