CN113085592A - 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
- Publication number
- CN113085592A CN113085592A CN202110391164.1A CN202110391164A CN113085592A CN 113085592 A CN113085592 A CN 113085592A CN 202110391164 A CN202110391164 A CN 202110391164A CN 113085592 A CN113085592 A CN 113085592A
- Authority
- CN
- China
- Prior art keywords
- fuel cell
- data
- driving range
- battery pack
- power battery
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 239000000446 fuel Substances 0.000 title claims abstract description 102
- UFHFLCQGNIYNRP-UHFFFAOYSA-N Hydrogen Chemical compound [H][H] UFHFLCQGNIYNRP-UHFFFAOYSA-N 0.000 title claims abstract description 82
- 239000001257 hydrogen Substances 0.000 title claims abstract description 82
- 229910052739 hydrogen Inorganic materials 0.000 title claims abstract description 82
- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000012544 monitoring process Methods 0.000 claims abstract description 22
- 239000013589 supplement Substances 0.000 claims abstract description 6
- 238000000611 regression analysis Methods 0.000 claims abstract description 3
- 238000012545 processing Methods 0.000 claims description 30
- 230000005540 biological transmission Effects 0.000 claims description 29
- 239000007789 gas Substances 0.000 claims description 26
- 230000008569 process Effects 0.000 claims description 12
- 238000007599 discharging Methods 0.000 claims description 11
- 238000004891 communication Methods 0.000 claims description 9
- 238000006243 chemical reaction Methods 0.000 claims description 5
- 230000036760 body temperature Effects 0.000 claims description 4
- 238000007781 pre-processing Methods 0.000 claims description 4
- 230000008859 change Effects 0.000 claims description 3
- 238000002360 preparation method Methods 0.000 claims description 3
- 230000006835 compression Effects 0.000 claims description 2
- 238000007906 compression Methods 0.000 claims description 2
- 238000012937 correction Methods 0.000 claims 1
- 208000019901 Anxiety disease Diseases 0.000 abstract description 4
- 230000036506 anxiety Effects 0.000 abstract description 4
- 238000004364 calculation method Methods 0.000 abstract description 3
- 230000002035 prolonged effect Effects 0.000 abstract 1
- 230000001133 acceleration Effects 0.000 description 4
- 230000007613 environmental effect Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000006399 behavior Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005265 energy consumption Methods 0.000 description 1
- 230000008020 evaporation Effects 0.000 description 1
- 238000001704 evaporation Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000000047 product Substances 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
Classifications
-
- 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
-
- 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
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Sustainable Development (AREA)
- Sustainable Energy (AREA)
- Power Engineering (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
- Fuel Cell (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, which comprises the following steps: s1, acquiring related data of a power battery pack of a hydrogen fuel cell dumper and residual data of a fuel cell; s2, detecting whether the acquired data are complete, if so, executing a step S3, otherwise, executing a step S4; s3, identifying the missing data, calling the historical data of the missing data for supplement, and then executing the step S4; s4, constructing a driving range prediction model; and S5, carrying out regression analysis on the acquired data through the driving range prediction model to obtain the current driving range prediction value of the dump truck. According to the invention, the driving range of the dump truck is predicted by monitoring various factors influencing the driving range of the hydrogen fuel cell dump truck in real time, so that the prediction accuracy is improved, the dump truck can be timely supplemented with energy when the energy of the dump truck is insufficient, the service life of the dump truck is prolonged, and the anxiety phenomenon of the range is relieved.
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 dump truck in real time.
Background
The hydrogen fuel cell dumper takes the fuel cell as a main energy source and the 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. The driving condition of the dump truck is severe, and the load capacity is large, so that the driving range of the dump truck is difficult to control by a driver. In the prior art, a driver approximately estimates the driving range of a vehicle by combining the hundred-kilometer energy consumption and the residual electric quantity of the hydrogen fuel cell dump truck, but the dump truck has larger error of an estimation result due to the variability of influence factors such as driving behaviors, terrain and the like of the driver and larger weight of the dump truck in the actual working process, and cannot accurately predict the driving range of the hydrogen fuel cell dump truck in real time.
Chinese patent publication No. CN112389213A discloses a driving range prediction method, device, apparatus, and storage medium, by which the driving range of a fuel cell and the driving range of a power cell can be integrated, and the influence of environmental factors such as weather conditions and road traffic conditions is taken into consideration, so that the driving range of a vehicle can be accurately predicted, and the problem of range anxiety of a driver can be alleviated.
However, in the above scheme, if the vehicle has a local fault, the driving range cannot be predicted, so that the application range of the prediction method is small.
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 technical scheme that:
the method for predicting the driving range of the hydrogen fuel cell dumper in real time comprises the following steps:
s1, acquiring related data of 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 so, executing a step S4, otherwise, executing a step S3;
s3, identifying the missing data, calling the historical data of the missing data for supplement, and then executing the step S4;
s4, constructing a driving range prediction model;
s5, after the step S4, carrying out regression analysis on the acquired data through the driving range prediction model to obtain the current driving range prediction value of the dump truck.
The invention comprises a method for predicting the driving range of a hydrogen fuel cell dumper in real time, which can more accurately predict the driving range of the dumper by monitoring various factors influencing the driving range of the hydrogen fuel cell dumper, such as related data of a power battery pack and residual data of a fuel cell in real time, and is used for prompting a driver to supplement energy in time, thereby prolonging the service life of a power supply system and relieving the problem of range anxiety. In addition, the prediction method can also confirm whether the dump truck has local fault or not by detecting corresponding missing data, and can still predict the driving range in real time when the dump truck has local fault.
Further, the method also includes step S6: after step S5, the data acquired at step S1 is added to the history data, and then the process returns to step S1.
Further, in step S1, the power battery pack related data includes total capacitance of the power battery pack, remaining capacity of the power battery pack, rate of change of remaining capacity of the power battery pack, depth of discharge of the power battery pack, temperature of the power battery pack, total voltage of charging and discharging of the power battery pack, total current of charging and discharging of the power battery pack, output power of the power battery pack, voltage of individual battery of the power battery pack, and depth of discharge of individual battery of the power battery pack.
Further, the method also includes step S7: after step S1, coordinating the power relationship between the power battery and the fuel cell by the power battery residue; wherein, step S7 physically includes:
s71, setting the allowance of the current power battery pack to be ASOCSetting the maximum margin safety value of the power battery pack to be AmaxSetting a minimum safety value A of the allowance of the power battery packmin(ii) a When A isSOC≥AmaxThen, step S62 is executed; when A isSOC≤AminThen, step S63 is executed; when A ismin<ASOC<AmaxThen, step S64 is executed;
s72, adjusting the output power of the fuel cell to enable the output power of the fuel cell to be lower than the load required 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 power demand of the driving motor of the dump truck, enabling the power battery pack and the fuel cell to work simultaneously, and enabling A to workSOC∈[A1,A2](ii) a Wherein [ A ]1,A2]The remaining capacity interval of the power battery pack in a healthy state is shown.
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 off-board environmental data includes travel gradient data; the vehicle body environment data comprises vehicle body temperature data, vehicle body pressure data, vehicle body speed data and hydrogen storage tank data.
Further, in step S1, the fuel cell remaining amount data is calculated by the gas tank pressure and the corrected gas state equation; the gas storage tank gas pressure and the corrected gas state equation are as follows:
in the formula, XBurning deviceRepresenting the current fuel cell residual of the dump truck, P representing the pressure in the hydrogen storage tank collected in real time, P0The pressure of the hydrogen storage tank indicating that the fuel cell has reached a minimum hydrogen consumption, V represents the volume of the hydrogen storage tank, and ZcIndicating gas compressionFactor, R represents the ideal gas constant, T represents the gas Kelvin temperature, η1Indicates the hydrogen utilization rate, eta, of the dump truck2Represents the hydrogen conversion,. eta3Indicating the efficiency of the power output.
Further, in step S4, the driving range prediction model is:
in the formula, LPreparation ofIndicating the predicted value of the current driving range of the dump truck, XiK representing the influence of the driving range of the dump truckiThe fitting parameters are indicated.
The invention also provides a system for predicting the driving range of the hydrogen fuel cell dumper in real time, which comprises the following components: the system comprises a sensing system, a battery monitoring system, a data transmission processing system and a network connection computing system, wherein the sensing system, the battery monitoring system and the network connection computing system are all in communication connection with the data transmission processing system.
The invention also comprises a system for predicting the driving range of the hydrogen fuel cell dump truck in real time, wherein the sensing system is used for acquiring the vehicle body environment data and the vehicle external environment data in the running process of the hydrogen fuel cell dump truck; 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; 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; and the internet computing system is used for predicting the data transmitted by the data transmission processing system to obtain the predicted value of the current driving range of the dump truck.
Preferably, the sensing system comprises a temperature sensing module, a pressure sensing module, an air 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 a hydrogen fuel cell dumper in real time, which can more accurately predict the driving range of the dumper by monitoring various factors influencing the driving range of the hydrogen fuel cell dumper, such as related data of a power battery pack and residual data of a fuel cell in real time, and is used for prompting a driver to supplement energy in time, thereby prolonging the service life of a power supply system and relieving the problem of range anxiety. In addition, the prediction method can also confirm whether the dump truck has local fault or not by detecting corresponding missing data, and can still predict the driving range in real time when the dump truck has local fault.
The invention also comprises a system for predicting the driving range of the hydrogen fuel cell dump truck in real time, wherein the sensing system is used for acquiring the vehicle body environment data and the vehicle external environment data in the running process of the hydrogen fuel cell dump truck; 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; 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; and the internet computing system is used for predicting the data transmitted by the data transmission processing system to obtain the predicted value of the current driving range of the dump truck.
Drawings
Fig. 1 is a flowchart of a method for predicting the driving range of a hydrogen fuel cell dump truck in real time according to an embodiment 1 of the present invention.
Fig. 2 is a flowchart of a method for predicting the driving range of a hydrogen fuel cell dump truck in real time according to embodiment 2 of the present invention.
Fig. 3 is a flowchart of a method for predicting the driving range of a hydrogen fuel cell dump truck in real time according to embodiment 3 of the present invention.
Fig. 4 is a schematic connection diagram of a system for predicting the driving range of a hydrogen fuel cell dump truck in real time according to the invention.
Detailed Description
The present invention will be further described with reference to the following embodiments. Wherein the showings are for the purpose of illustration only and are shown by way of illustration only and not in actual form, and are not to be construed as limiting the present patent; to better illustrate the embodiments of the present invention, some parts of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product; it will be understood 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 numerals in the drawings of the embodiments of the present invention correspond to the same or similar components; in the description of the present invention, it should be understood that if there is an orientation or positional relationship indicated by the terms "upper", "lower", "left", "right", etc. based on the orientation 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 intended to indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and therefore, the terms describing the positional relationship in the drawings are only used for illustrative purposes and are not to be construed as limiting the present patent, and the specific meaning of the terms may be understood by those skilled in the art according to specific circumstances.
Example 1
Fig. 1 shows a first embodiment of the method for predicting the driving range of a hydrogen fuel cell dump truck in real time according to the present invention, which includes the following steps:
s1, acquiring related data of a power battery pack, vehicle body environment data and vehicle exterior environment data of the hydrogen fuel cell dumper through a sensing system, and acquiring fuel cell remaining data through calculation and analysis.
The relevant data of the power battery pack comprise the total capacitance of the power battery pack, the residual capacity (SOC) of the power battery pack, the change rate of the residual capacity (SOC) of the power battery pack, the discharge depth of the power battery pack, the temperature of the power battery pack, the total charge-discharge voltage of the power battery pack, the total charge-discharge current of the power battery pack, the output power of the power battery pack, the voltage of a single battery of the power battery pack and the discharge depth of a single battery of the power battery pack. The relevant data of the power battery pack are acquired in real time through a CAN bus, and specifically, the relevant data of the power battery pack are transmitted to a battery monitoring system through the CAN bus and then transmitted to a data transmission processing system through the battery monitoring system.
Wherein, the fuel cell residual data is calculated by the gas pressure of the gas storage tank and a corrected gas state equation; the gas storage tank pressure and the corrected gas state equation are as follows:
in the formula, XBurning deviceRepresenting the current fuel cell residual of the dump truck, P representing the pressure in the hydrogen storage tank collected in real time, P0The pressure of the hydrogen storage tank indicating that the fuel cell has reached a minimum hydrogen consumption, V represents the volume of the hydrogen storage tank, and ZcRepresenting the gas compression factor, R representing the ideal gas constant, T representing the gas Kelvin temperature, η1Indicates the hydrogen utilization rate, eta, of the dump truck2Represents the hydrogen conversion,. eta3Indicating the efficiency of the power output. The pressure in the hydrogen storage tank acquired in real time and represented by P can be acquired in real time through the air pressure sensor.
It should be noted that, in the process of inputting hydrogen into the fuel cell, a part of the hydrogen is used for supplying energy to some electrical devices mounted on the dump truck, so that the fuel cell has the problem of high conversion rate when the chemical energy of the hydrogen is converted into electric energy, and after the electric energy is generated, only a part of the electric energy is used for driving the dump truck of the hydrogen fuel cell to run, so that the residual data of the fuel cell can be calculated through the air pressure of the air storage tank and the corrected gas state equation.
The vehicle body environment data comprises vehicle body temperature data, vehicle body pressure data, vehicle body speed data and hydrogen storage tank data. The temperature data of the vehicle body is acquired through a temperature sensor, the pressure data of the vehicle body is acquired through a pressure sensor, the speed data of the vehicle body is acquired through a speed sensor, and the data of the hydrogen storage tank is acquired through an air pressure sensor.
Specifically, the vehicle body temperature data includes a vehicle body outside temperature, an air conditioner temperature; the external temperature of the vehicle body is obtained in real time by installing the temperature sensor outside the vehicle body, and the temperature of the air conditioner is obtained in real time by installing the temperature sensor on the air conditioner evaporation box.
Specifically, the body pressure data includes the dump truck load, the running resistance, and the running acceleration resistance; the load, the running resistance and the running acceleration resistance of the dump truck are all acquired in real time through the pressure sensor;
specifically, the vehicle body speed data includes a dump truck running vehicle speed and running 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 allowance of the hydrogen storage tank; the air pressure in the hydrogen storage tank bottle and the residual amount of the hydrogen storage tank are obtained in real time through the air pressure sensor.
Specifically, the off-board environment data includes traveling gradient data; the traveling gradient data is acquired in real time by a gradient sensor.
And the data acquired by each sensor is sent to a data transmission processing system according to a preset communication protocol. The types of data acquired by the sensors may be increased or decreased according to actual conditions, and the selection of the data type is merely preferable.
And S2, the data transmission processing system receives and classifies the data sent by the sensing system, then the data transmission processing system detects whether the data acquired in the step S1 are complete, if so, the step S4 is executed, and if not, the step S3 is executed.
It should be noted that the integrity of the acquired data can be set according to actual situations. The integrity of the data in the embodiment refers to that the power battery pack related data, the fuel cell residual data, the vehicle body environment data and the vehicle external environment data of the hydrogen fuel cell dump truck are all absent.
And S3, identifying the missing data through the data transmission processing system, calling recent historical data stored under the classification of the missing data in the data transmission processing system for supplement, uploading the recent historical data to the internet computing system in real time, and then executing the step S4. And the data transmission processing system can also find out corresponding fault parts according to the missing data and display the fault parts on the vehicle-mounted display system, so as to prompt a driver to repair the fault parts.
It should be noted that the recent history data refers to data of the same day and the same time in the last week of the current time node as history data, and is uploaded to the networked computing system together with other data received in real time. However, the selected historical data time node is only preferable, and can be selected and set according to actual conditions.
S4, constructing a driving range prediction model through a network connection computing system; wherein, the driving range prediction model is as follows:
in the formula, LPreparation ofIndicating the predicted value of the current driving range of the dump truck, XiK representing the influence of the driving range of the dump truckiThe fitting parameters are indicated.
And S5, after the step S4, the internet computing system receives the data transmitted by the data transmission processing system in real time, substitutes the data into the driving range prediction model for fitting to obtain the predicted value of the current driving range of the dump truck, transmits the predicted value to the data transmission processing system, and transmits the data transmission processing system to the vehicle-mounted display system for displaying.
The influence of factors such as the power battery state of the hydrogen fuel cell dump truck, the fuel battery residual capacity, the load of the dump truck, the external environment temperature and the like on the driving range is comprehensively considered, the driving range prediction model is used for predicting, the prediction accuracy and the fitting goodness can be higher, and the driving range of the hydrogen fuel cell 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 step S6: after step S5, the data acquired at step S1 is added to the history data by data transfer processing system classification, and then returns to step S1.
Specifically, after each prediction is finished, the data transmission processing system adds various data collected in real time into the historical data, a new driving range prediction model is fitted after the data are updated so as to realize the real-time update of the model, 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 power relationship between the power battery and the fuel cell by the power battery residue; wherein, step S7 physically includes:
s71, setting the allowance of the current power battery pack to be ASOCSetting the maximum margin safety value of the power battery pack to be AmaxSetting a minimum safety value A of the allowance of the power battery packmin；
When A isSOC≥AmaxThen, step S72 is executed: adjusting the output power of the fuel cell to make the output power of the fuel cell lower than the load demand power of a driving motor of the dump truck;
when A isSOC≤AminThen, step S73 is executed: adjusting the output power of the fuel cell to enable the fuel cell to work at the maximum output power;
when A ismin<ASOC<AmaxThen, step S74 is executed: adjusting the output power of the fuel cell according to the load power demand of the driving motor of the dump truck, enabling the power battery pack and the fuel cell to work simultaneously, and enabling A to work simultaneouslySOC∈[A1,A2](ii) a Wherein [ A ]1,A2]The remaining capacity interval of the power battery pack in a healthy state is shown.
The rotating speed torque of the driving motor of the dump truck is obtained through the rotating speed torque sensor, and then the required load power of the driving motor of the dump truck is obtained.
Step S7 and steps S2 to S6 are not in the order, and step S7 may be performed at any time of steps S2 to S6.
Example 4
Fig. 4 shows a first embodiment of the system for predicting the driving range of a hydrogen fuel cell dump truck in real time according to the present invention, which includes:
the sensing system is used for acquiring vehicle body environment data and vehicle external environment data in the running process of the hydrogen fuel cell dump truck;
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 coordinating the energy supply relationship 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 a predicted value of the current driving range of the dump truck;
the sensing system, the battery monitoring system and the network connection 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, an air 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.
When the battery monitoring system is used for coordinating the energy supply relationship between the power battery pack and the fuel battery, the battery monitoring system is realized by monitoring and adjusting the residual capacity (SOC) of the power battery pack: firstly, setting a maximum safety value and a minimum safety value of the allowance of the power battery pack;
when the residual capacity (SOC) of the power battery pack is equal to or greater than the maximum safety value of the residual capacity of the power battery pack, if the power battery pack is continuously charged, an overcharge phenomenon can be caused, and the power battery pack is damaged; at the moment, the output power of the fuel cell is adjusted through the battery monitoring system, so that the output power of the fuel cell is slightly lower than the load required power of a driving motor of the dump truck; the power battery pack participates in energy supply and is used as an auxiliary energy source to drive the dump truck to run, and the power battery pack is in a discharging state at the moment, so that the power battery pack can be prevented from being overcharged;
when the residual capacity (SOC) of the power battery pack is equal to or less than the minimum safety value of the residual capacity of the power battery pack, if the power battery pack continues to discharge, an over-discharge phenomenon can be caused; at the moment, the output power of the fuel cell is improved through the battery 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 over-discharging, and the power battery pack is protected;
when the residual capacity (SOC) of the power battery pack is between the maximum safety value and the minimum safety value, the power battery pack and the fuel cell work simultaneously by combining the requirement of the power demanded by the load of the actual dump truck driving motor, and the charging and discharging of the power battery pack are carried out simultaneously and are maintained near the current SOC value.
It should be noted that the maximum safety value and the minimum safety value of the remaining capacity of the power battery pack can be set according to actual conditions.
Furthermore, as shown in fig. 4, the prediction system further includes an on-board display system for displaying various items of data, and the on-board display system is connected with the data transmission processing system in a communication manner. The vehicle-mounted display system in the embodiment is a vehicle-mounted display screen, and the vehicle-mounted display screen can be used for displaying the predicted value of the current driving range of the dump truck and can also be used for displaying the name of a corresponding fault component found according to missing data.
Example 5
The embodiment is similar to the embodiment 4, except that the system in the embodiment further includes a positioning system in communication connection with the data transmission processing system, and the positioning system can be used for acquiring current driving road condition data of the dump truck and then uploading the data to the data transmission processing system.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (10)
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 related data of 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 so, executing a step S4, otherwise, executing a step S3;
s3, identifying the missing data, calling the historical data of the missing data for supplement, and then executing the step S4;
s4, constructing a driving range prediction model;
s5, after the step S4, carrying out regression analysis on the acquired data through the driving range prediction model to obtain the current driving range prediction value of the dump truck.
2. The method for predicting the driving range of the hydrogen fuel cell self-discharging vehicle in real time as set forth in claim 1, further comprising the step S6 of: after step S5, the data acquired at step S1 is added to the history data, and then the process returns to step S1.
3. The method for predicting the driving range of a hydrogen fuel cell dumper in real time as recited in claim 1, wherein the power battery pack related data comprises total capacity of the power battery pack, remaining capacity of the power battery pack, rate of change of the remaining capacity of the power battery pack, depth of discharge of the power battery pack, temperature of the power battery pack, total voltage of charge and discharge of the power battery pack, total current of charge and discharge of the power battery pack, output power of the power battery pack, voltage of single battery of the power battery pack, and depth of discharge of single battery of the power battery pack in step S1.
4. The method for predicting the driving range of the hydrogen fuel cell self-discharging vehicle in real time as set forth in claim 1, further comprising the step S7 of: after step S1, coordinating the power relationship between the power battery and the fuel cell by the power battery residue; wherein, step S7 physically includes:
s71, setting the allowance of the current power battery pack to be ASOCIf a power battery packMargin maximum safety value of AmaxSetting a minimum safety value A of the allowance of the power battery packmin(ii) a When A isSOC≥AmaxThen, step S72 is executed; when A isSOC≤AminThen, step S73 is executed; when A ismin<ASOC<AmaxThen, step S74 is executed;
s72, adjusting the output power of the fuel cell to enable the output power of the fuel cell to be lower than the load required 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 enable A to workSOC∈[A1,A2](ii) a Wherein [ A ]1,A2]The remaining capacity interval of the power battery pack in a healthy state is shown.
5. The method for predicting the driving range of the hydrogen fuel cell self-discharging vehicle in real time as set forth in claim 1, wherein in the step S1, the method further comprises acquiring vehicle body environment data and vehicle exterior environment data of the hydrogen fuel cell self-discharging vehicle.
6. The method for predicting the driving range of the hydrogen fuel cell self-dumping truck in real time according to claim 5, wherein the vehicle external environment data comprises driving gradient data; the vehicle body environment data comprises vehicle body temperature data, vehicle body pressure data, vehicle body speed data and hydrogen storage tank data.
7. The method for predicting the driving range of the hydrogen fuel cell self-discharging vehicle in real time as claimed in claim 1, wherein in step S1, the fuel cell residual data is calculated by the gas pressure of the gas storage tank and the state equation of the correction gas; the gas storage tank gas pressure and the corrected gas state equation are as follows:
in the formula, XBurning deviceRepresenting the current fuel cell residual of the dump truck, P representing the pressure in the hydrogen storage tank collected in real time, P0The pressure of the hydrogen storage tank indicating that the fuel cell has reached a minimum hydrogen consumption, V represents the volume of the hydrogen storage tank, and ZcRepresenting the gas compression factor, R representing the ideal gas constant, T representing the gas Kelvin temperature, η1Indicates the hydrogen utilization rate, eta, of the dump truck2Represents the hydrogen conversion,. eta3Indicating the efficiency of the power output.
8. The method for predicting the driving range of the hydrogen fuel cell self-discharging vehicle in real time according to claim 1, wherein in step S4, the driving range prediction model is:
in the formula, LPreparation ofIndicating the predicted value of the current driving range of the dump truck, XiK representing the influence of the driving range of the dump truckiThe fitting parameters are indicated.
9. A system for predicting the driving range of a hydrogen fuel cell dumper in real time is characterized by comprising the following components:
the sensing system is used for acquiring vehicle body environment data and vehicle external environment data in the running process of the hydrogen fuel cell dump truck;
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;
the data transmission processing system is used for preprocessing, classifying and storing various types of 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 a predicted value of the current driving range of the dump truck;
and the sensing system, the battery monitoring system and the network connection computing system are all in communication connection with the data transmission processing system.
10. The system for predicting the driving range of the hydrogen fuel cell dumper in real time according to claim 9, wherein the sensing system comprises a temperature sensing module, a pressure sensing module, an air pressure sensing module, a speed sensing module and a gradient sensing module which are in communication connection with a data transmission and processing system.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110391164.1A CN113085592B (en) | 2021-04-12 | 2021-04-12 | Method and system for predicting driving range of hydrogen fuel cell dump truck in real time |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110391164.1A CN113085592B (en) | 2021-04-12 | 2021-04-12 | Method and system for predicting driving range of hydrogen fuel cell dump truck in real time |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113085592A true CN113085592A (en) | 2021-07-09 |
| CN113085592B CN113085592B (en) | 2024-04-12 |
Family
ID=76676326
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110391164.1A Active CN113085592B (en) | 2021-04-12 | 2021-04-12 | Method and system for predicting driving range of hydrogen fuel cell dump truck in real time |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113085592B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114136342A (en) * | 2021-11-30 | 2022-03-04 | 深圳市明睿数据科技有限公司 | Mileage tampering judgment method and system |
| CN115583166A (en) * | 2022-10-14 | 2023-01-10 | 中铁武汉电气化局集团科工装备有限公司 | Comprehensive energy monitoring and management system of hydrogen energy operation vehicle |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103247177A (en) * | 2013-05-21 | 2013-08-14 | 清华大学 | Large-scale road network traffic flow real-time dynamic prediction system |
| CN107225985A (en) * | 2017-05-08 | 2017-10-03 | 江苏理工学院 | A kind of real-time predicting method of hydrogen cell automobile remaining mileage |
| CN108556682A (en) * | 2018-03-30 | 2018-09-21 | 北京新能源汽车股份有限公司 | A kind of continual mileage prediction technique, device and equipment |
| CN112046486A (en) * | 2020-08-17 | 2020-12-08 | 武汉理工大学 | Fuel cell automobile output power correction method, system and storage medium |
| CN112389213A (en) * | 2020-11-25 | 2021-02-23 | 中国第一汽车股份有限公司 | Driving range prediction method, device, equipment and storage medium |
-
2021
- 2021-04-12 CN CN202110391164.1A patent/CN113085592B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103247177A (en) * | 2013-05-21 | 2013-08-14 | 清华大学 | Large-scale road network traffic flow real-time dynamic prediction system |
| CN107225985A (en) * | 2017-05-08 | 2017-10-03 | 江苏理工学院 | A kind of real-time predicting method of hydrogen cell automobile remaining mileage |
| CN108556682A (en) * | 2018-03-30 | 2018-09-21 | 北京新能源汽车股份有限公司 | A kind of continual mileage prediction technique, device and equipment |
| CN112046486A (en) * | 2020-08-17 | 2020-12-08 | 武汉理工大学 | Fuel cell automobile output power correction method, system and storage medium |
| CN112389213A (en) * | 2020-11-25 | 2021-02-23 | 中国第一汽车股份有限公司 | Driving range prediction method, device, equipment and storage medium |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114136342A (en) * | 2021-11-30 | 2022-03-04 | 深圳市明睿数据科技有限公司 | Mileage tampering judgment method and system |
| CN114136342B (en) * | 2021-11-30 | 2024-03-22 | 深圳市明睿数据科技有限公司 | Mileage tampering judging method and system |
| CN115583166A (en) * | 2022-10-14 | 2023-01-10 | 中铁武汉电气化局集团科工装备有限公司 | Comprehensive energy monitoring and management system of hydrogen energy operation vehicle |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113085592B (en) | 2024-04-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Ebbesen et al. | Battery state-of-health perceptive energy management for hybrid electric vehicles | |
| US8791810B2 (en) | Optimal electric vehicle battery recommendation system | |
| CN103687749B (en) | Systems and methods for controlling multiple storage devices | |
| JP7337781B2 (en) | State-of-Charge Estimation System for Power Storage Device | |
| US9994115B2 (en) | Battery pack replacement system for electric vehicle with energy storage system | |
| EP2309619A1 (en) | Imbalance reduction circuit, power supply device, and imbalance reduction method | |
| JP6488562B2 (en) | Battery and charging device management system, method, and charging device | |
| CN113085592B (en) | Method and system for predicting driving range of hydrogen fuel cell dump truck in real time | |
| Waseem et al. | Battery technologies and functionality of battery management system for EVs: Current status, key challenges, and future prospectives | |
| CN102089956A (en) | Battery charge/discharge control device and hybrid vehicle using the same | |
| JP7040601B2 (en) | Battery control device, battery control method, uninterruptible power supply, power system and electric vehicle | |
| CN113581019B (en) | Energy management method for hybrid drive unmanned mining truck | |
| CN103155347A (en) | Charging apparatus, power storage apparatus, and power source apparatus | |
| CN111591152B (en) | Battery pack power change decision method, device and system in charge and change separation mode | |
| EP3585642B1 (en) | A method and arrangement for balancing a battery pack | |
| CN106042960B (en) | Judge the abnormal device and method of battery charging according to battery characteristics value changes | |
| CN114789675A (en) | Device and method for determining an action to be taken and at least partially electric vehicle | |
| US20160355162A1 (en) | Method of using battery pack for electric vehicle | |
| Ali et al. | Intelligent real-time power management of multi-source HEVs based on driving state recognition and offline optimization | |
| CN115071490A (en) | Control system and energy management method | |
| CN103112361A (en) | Automobile battery used as sensing node and electric automobile provided with the same | |
| CN105751909B (en) | A kind of Mobile portable formula electric automobile power battery group and its method of work | |
| EP4209379A1 (en) | Method, device and system for vehicle power battery auxiliary equilibrium | |
| CN108666638A (en) | A kind of battery module and its Energy Management System and method | |
| CN111610459B (en) | System, method and storage medium for predicting discharge curve of battery pack |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |