CN109613905B - Method and device for dynamically identifying actual operation high-oil-consumption severe working condition of heavy commercial vehicle - Google Patents
Method and device for dynamically identifying actual operation high-oil-consumption severe working condition of heavy commercial vehicle Download PDFInfo
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Abstract
The invention discloses a good device for dynamically identifying the actual operation high oil consumption severe working condition of a heavy commercial vehicle. The invention provides a method for diagnosing and extracting a high-oil-consumption severe working condition during actual operation of a heavy commercial vehicle, aiming at the problem of the high-oil-consumption working condition during the actual operation of the heavy commercial vehicle, and provides technical support for an enterprise to optimize and improve a control strategy for the high-oil-consumption severe working condition region during the actual operation of the heavy commercial vehicle.
Description
Technical Field
The invention discloses a method and a device for realizing dynamic diagnosis and extracting high-oil-consumption severe working conditions of actual operation of a heavy commercial vehicle based on a vehicle-mounted terminal online monitoring system, and belongs to the dynamic diagnosis and extraction technology of the high-oil-consumption severe working conditions of the actual operation of the heavy commercial vehicle.
Background
In 2017, the automobile yield of China is 2901.5 thousands, the sales volume is 2887.9 thousands, and the automobile yield and sales volume is the first global automobile yield and sales volume of cicada union in 9 continuous years. After a continuous high-speed growth of more than ten years, the Chinese automobile market enters a steady and continuous growth period. With the rapid increase of automobile production and sales and automobile inventory in China, the energy demand in China is gradually increased, and the petroleum consumption is the most important factor. The number of the national statistical bureau shows that in 2014, the annual oil consumption of China firstly breaks through 5 hundred million tons, although the oil yield of China steadily rises every year, the oil consumption still falls behind the foot of the increase of oil consumption, the external dependence of China in 2009 is firstly over 50%, and then the oil consumption still continues to be high, even reaches 59.34% in 2014, and the oil consumption forms a huge threat to the energy safety of China. The quantity of heavy commercial vehicles in China is much less than that of passenger vehicles, but the fuel oil consumed by the heavy commercial vehicles is generally equivalent to that of the passenger vehicles. Because the proportion of the oil consumption of the heavy commercial vehicle in China to the oil consumption of the vehicle is the largest, the urgency of oil consumption management is stronger than that of any country. If the oil consumption of the heavy commercial vehicle is reduced by 10%, at least 900 million tons of gasoline and diesel oil can be saved every year even if the oil consumption is measured according to the reserved quantity of 1400 million heavy commercial vehicles at the end of 2012, which is equivalent to the fuel consumption of 900 million household cars, and the oil saving effect is huge.
Energy conservation and pollutant prevention and control of heavy commercial vehicles are the core problems of green development of motor vehicles in China. With the stricter regulations on energy consumption and emission, the heavy commercial vehicle faces more challenges on the optimization of the energy-saving and emission-reducing technology. NO of motor vehicle actual operation condition in ChinaXEmissions promulgated a number of regulatory standards, particularly in 2017, up to eight standard documents or solicitations related to the actual emissions regulation of heavy commercial vehicles, which were tightly promulgated or about to be promulgated by the national or local governments. In 2017, in 4 months, a GB3847 solicited comment draft is issued; 7, issuing HJ 845-; 10 months, issuing HJ 857 and 2017 vehicle-mounted measurement method and technical requirements for exhaust pollutants of heavy-duty diesel vehicles and gas fuel vehicles; in particular, in 12 months in 2017, the Beijing environmental protection agency simultaneously issued DB11/965 and 2017 emission limits and measurement methods (IV and V stages of an on-board method), DB11/1475 and 2017 emission limits and measurement methods (IV and V stages of an OBD method), and DB11/1476 and 2017 rapid detection methods and emission limits for nitrogen oxides of heavy vehicles, and implemented in 20 months 12 and 20 months in 2017. The standard regulations relate to the detection of the actual running emission of the heavy commercial vehicle, and show that the environmental protection department pays more and more attention to the actual emission regulation of the heavy commercial vehicle and is stricter and stricter. The implementation of these regulations provides an all-round regulation of the actual operating emissions of heavy commercial vehicles.
The key points of the management of the pollution emission control of the motor vehicle are basically turned to actual operation supervision, and a monitoring network of a plurality of detection technologies in full time and space is gradually formed. However, the monitoring on the oil consumption of the heavy commercial vehicle still stays in a complete vehicle drum test room, GB/T27840-2011 'measuring method for fuel consumption of the heavy commercial vehicle' stipulates that the heavy commercial vehicle adopts C-WTVVC working condition to measure the fuel consumption, and GB 30510-. However, in actual use, the fuel consumption of heavy-duty commercial vehicles is higher than the fuel consumption value of type certification, which is common in the whole automobile industry. Therefore, under the requirements of the existing fuel consumption measuring method and limit value, the high oil consumption working condition of the heavy commercial vehicle in actual operation is diagnosed and extracted for supporting the optimization and calibration of the vehicle fuel economy, meeting the fuel economy of the vehicle in actual use, effectively reducing the fuel consumption of the heavy commercial vehicle and being beneficial to reducing the consumption of petroleum energy in the whole automobile industry.
The invention discloses a method and a device for dynamically diagnosing a high-oil-consumption working condition, which are used for monitoring the actual running fuel consumption and related running parameters of a heavy commercial vehicle by using a vehicle-mounted terminal online monitoring system.
Disclosure of Invention
According to the invention, the vehicle-mounted terminal online monitoring system is installed on the OBD diagnosis interface of the heavy commercial vehicle, signals such as the actual running speed of the heavy commercial vehicle, the running state parameters of a diesel engine, the fuel flow of an engine and the like are collected in real time, the collected data information is uploaded to the cloud monitoring platform in real time through the GPRS technology, a diagnosis module and a high-oil-consumption severe working condition extraction module of the heavy commercial vehicle under the actual running high-oil-consumption severe working condition are designed in the cloud monitoring platform and are stored in a database in real time, and the dynamic diagnosis and extraction of the actual running high-oil-consumption severe working condition of the heavy commercial vehicle are realized.
The invention firstly requests to protect a method for dynamically identifying the actual operation high-oil-consumption severe working condition of a heavy commercial vehicle, which is characterized by comprising the following steps of:
a: the method comprises the steps that a vehicle-mounted terminal online monitoring system is installed on an OBD diagnosis interface of the heavy commercial vehicle, and signals of the actual running speed of the heavy commercial vehicle, running state parameters of a diesel engine, the fuel flow of the engine and the like are collected in real time;
b: the collected signal data information of the actual running vehicle speed of the heavy commercial vehicle, the running state parameters of the diesel engine, the fuel flow of the engine and the like is uploaded to a cloud monitoring platform in real time through a GPRS technology;
c: according to a high-oil-consumption severe working condition diagnosis model which is designed in a cloud monitoring platform and is actually operated by the heavy commercial vehicle, a diagnosis algorithm is adopted to diagnose the oil consumption of the heavy commercial vehicle in real time and identify the high-oil-consumption working condition;
d: the method comprises the steps of adopting a diagnosis algorithm to carry out real-time diagnosis on oil consumption of the heavy commercial vehicle and extracting data after high oil consumption working condition identification through a cloud monitoring platform, storing extracted high oil consumption segments and synchronous monitoring data stream information in a cellular data form, and numbering.
Preferably, in the step a, a vehicle-mounted terminal online monitoring system is installed on an OBD diagnostic interface of the heavy commercial vehicle, and signal requirements such as the vehicle speed, the diesel engine running state parameters, and the engine fuel flow of the actual running of the heavy commercial vehicle are acquired in real time and are satisfied: the frequency of the collected data of the vehicle speed is 1 Hz.
Further, according to the diagnosis model for the heavy commercial vehicle actually running under the high oil consumption severe working condition designed in the cloud monitoring platform in the step C, the oil consumption of the heavy commercial vehicle is diagnosed in real time and identified by a diagnosis algorithm, and the diagnosis algorithm specifically comprises the following steps:
step 1: dividing working conditions;
step 2: calculating the oil consumption of the short working condition segment;
and step 3: calculating a relative oil consumption factor;
and 4, step 4: high oil consumption fraction diagnosis.
Further, the step D: the method for extracting the data after real-time diagnosis and high-oil-consumption working condition identification of the oil consumption of the heavy commercial vehicle by using the diagnostic algorithm comprises the following steps of extracting high-oil-consumption segments and synchronous monitoring data stream information, storing the working condition segment data information in a cellular data form, and before numbering, further comprising:
will be marked as FHiThe high-oil-consumption severe working condition segment and the synchronous data flow information thereof are extracted from the original data flow in a data group form.
Further, the step D: the method for extracting the data after real-time diagnosis and high-oil-consumption working condition identification of the oil consumption of the heavy commercial vehicle by using the diagnostic algorithm comprises the following steps of extracting high-oil-consumption segments and synchronous monitoring data stream information, storing the working condition segment data information in a cellular data form, numbering the working condition segment data information, and further comprising the following steps of:
the high oil consumption segments are extracted according to the relative oil consumption factor, and analysis functions such as relevant vehicle working condition analysis and engine working condition analysis can be performed.
The invention also requests to protect a device for dynamically identifying the actual running high-oil-consumption severe working condition of the heavy commercial vehicle, which is characterized by comprising the following steps of: the system comprises a vehicle-mounted terminal on-line monitoring system, a cloud monitoring platform and a database repository, wherein,
the vehicle-mounted terminal online monitoring system is installed at an OBD diagnosis interface of the diesel vehicle and is used for acquiring signals such as the actual running speed of the heavy commercial vehicle, the running state parameters of the diesel engine, the fuel flow of the engine and the like in real time;
the cloud monitoring platform can realize the functions of receiving, diagnosing, extracting working conditions and storing a database of data acquired by the vehicle-mounted terminal on-line monitoring system, receives and uploads the acquired signals of the actual running speed of the heavy commercial vehicle, the running state parameters of the diesel engine, the fuel flow of the engine and the like in real time through the GPRS technology, and further according to a high-oil-consumption severe working condition diagnosis model which is designed in the cloud monitoring platform and is actually operated by the heavy commercial vehicle, real-time diagnosis and high-oil-consumption working condition recognition are carried out on the oil consumption of the heavy commercial vehicle by adopting a diagnosis algorithm, data obtained after the real-time diagnosis and the high-oil-consumption working condition recognition of the oil consumption of the heavy commercial vehicle by adopting the diagnosis algorithm are extracted through the cloud monitoring platform, the extracted high-oil-consumption segments and the synchronous monitoring data flow information are stored in a cellular data form, and the working condition segment data information is numbered.
The invention provides a method for diagnosing and extracting a high-oil-consumption severe working condition during actual operation of a heavy commercial vehicle, aiming at the problem of the high-oil-consumption working condition during the actual operation of the heavy commercial vehicle, and provides technical support for an enterprise to optimize and improve a control strategy for the high-oil-consumption severe working condition region during the actual operation of the heavy commercial vehicle.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosed subject matter, are incorporated in and constitute a part of this specification. The drawings illustrate the implementations of the disclosed subject matter and, together with the detailed description, serve to explain the principles of implementations of the disclosed subject matter. No attempt is made to show structural details of the disclosed subject matter in more detail than is necessary for a fundamental understanding of the disclosed subject matter and various modes of practicing the same.
FIG. 1 is a flow chart illustrating a method for dynamically identifying the actual high-fuel-consumption severe operating condition of a heavy-duty commercial vehicle, which is claimed by the present invention;
fig. 2 is a block diagram of a device for dynamically identifying the actual running high-fuel-consumption severe operating condition of a heavy-duty commercial vehicle, which is claimed by the invention.
Detailed Description
The advantages, features and methods of accomplishing the same will become apparent from the drawings and the detailed description that follows.
Referring to the attached drawing 1, the invention firstly requests to protect a method for dynamically identifying the actual operation high-oil-consumption severe working condition of a heavy commercial vehicle, and is characterized in that:
a: the method comprises the steps that a vehicle-mounted terminal online monitoring system is installed on an OBD diagnosis interface of the heavy commercial vehicle, and signals of the actual running speed of the heavy commercial vehicle, running state parameters of a diesel engine, the fuel flow of the engine and the like are collected in real time;
b: the collected signal data information of the actual running vehicle speed of the heavy commercial vehicle, the running state parameters of the diesel engine, the fuel flow of the engine and the like is uploaded to a cloud monitoring platform in real time through a GPRS technology;
c: according to a high-oil-consumption severe working condition diagnosis model which is designed in a cloud monitoring platform and is actually operated by the heavy commercial vehicle, a diagnosis algorithm is adopted to diagnose the oil consumption of the heavy commercial vehicle in real time and identify the high-oil-consumption working condition;
d: the method comprises the steps of adopting a diagnosis algorithm to carry out real-time diagnosis on oil consumption of the heavy commercial vehicle and extracting data after high oil consumption working condition identification through a cloud monitoring platform, storing extracted high oil consumption segments and synchronous monitoring data stream information in a cellular data form, and numbering.
The vehicle-mounted terminal online monitoring system is installed on an OBD diagnosis interface of the heavy commercial vehicle, signals such as the actual running speed of the heavy commercial vehicle, the running state parameters of a diesel engine and the flow of engine fuel are collected in real time, collected data information is uploaded to a cloud monitoring platform in real time through a GPRS technology, a diagnosis module of the actual running high-oil-consumption severe working condition of the heavy commercial vehicle and an extraction module of the high-oil-consumption severe working condition are designed in the cloud monitoring platform, and are stored in a database in real time, so that the dynamic diagnosis and extraction of the actual running high-oil-consumption severe working condition of the heavy commercial vehicle are realized.
The vehicle-mounted terminal on-line monitoring system at least meets the requirements of vehicle and engine working condition parameters and fuel flow data acquisition and acquisition frequency in the table 1. (refer to DB11/1475 appendix G of 2017 emission limits and measurement methods (OBD method stages IV and V) for heavy-duty vehicle exhaust pollutants).
TABLE 1 data and frequency requirements collected by the on-line monitoring system of the vehicle-mounted terminal
Further, according to the diagnosis model for the heavy commercial vehicle actually running under the high oil consumption severe working condition designed in the cloud monitoring platform in the step C, the oil consumption of the heavy commercial vehicle is diagnosed in real time and identified by a diagnosis algorithm, and the diagnosis algorithm specifically comprises the following steps: continuously monitoring vehicle operation parameters and fuel flow, and completing once oil consumption diagnosis within 5min
Step 1: dividing working conditions; the specific power VSP and the instantaneous speed v are selected as the characteristic parameters of the vehicle transient working condition mode, and the calculation formula of the VSP is shown in the formula (1).
VSP＝v(1.1a+0.132)+0.000302v3(1)
In the formula, VSP is the specific power of the vehicle, kW/t; v is the vehicle running speed, m/s; a is the instantaneous acceleration of the vehicle, m/s2。
And determining the section division of the VSP Bin section in the microscopic operation mode by referring to the analysis method of the emission data of the heavy vehicles of MOVES. The VSP Bin interval of the vehicle is determined according to different running states (deceleration, idling, acceleration and uniform speed) of the vehicle and instantaneous VSP data. The running state of the vehicle is divided into: decelerating, idling, 0-40 km/h, 40-80km/h and more than 80km/h for 5 speed sections; the dividing intervals of the VSP are started from less than or equal to-8 kW/t, the increment is 2kW/t, the increment is increased to more than 12kW/t, and the total interval is 12 intervals. Thus VSP Bin is determined to be 38 bins from the vehicle operating conditions and VSP combined profile, see Table 1. Wherein Bin0 and Bin1 respectively represent deceleration and idle speed sections, Bin2-13 is a low-speed (less than 40km/h) section, Bin14-25 is a medium-speed (40-80km/h) section, and Bin26-37 is a high-speed (more than 80km/h) section. Based on VSP Bin, dividing the instantaneous working point into different VSP bins according to the dividing basis meeting Bin according to the vehicle speed, the acceleration and the VSP value of the instantaneous working point, and dividing information streams such as the oil consumption value, the engine rotating speed and the torque of the instantaneous working point into corresponding bins along with the working point.
The key point of the invention is that the average hundred kilometer oil consumption of 5min short-time traffic flow which belongs to different VSP bins is respectively calculated, the working condition proportion of the working condition of a standard test cycle C-WTVVC which belongs to different VSP bins of an oil consumption rule is calculated, the product of the average hundred kilometer oil consumption of each VSP Bin and the working condition proportion of the working condition of the C-WTVVC in the VSP Bin is summed, and the average hundred kilometer oil consumption of 5min short-time traffic flow which is normalized to the C-WTVVC is obtained. The invention is innovative in that a 5min short-time traffic flow monitored in real time is normalized to a C-WTVVC working condition for oil consumption detection based on VSP Bin, and is compared with a standard oil consumption limit value of a rule to judge whether the real-time working condition oil consumption belongs to a high oil consumption working condition or not.
TABLE 2 v-VSP partitioning
Step 2: calculating the oil consumption of the short working condition segment;
dividing the running working condition and oil consumption data of the vehicle in each 5min short segment into a microscopic running mode Bin corresponding to the v-VSP, calculating the oil consumption of all transient working condition points in each Bin, and obtaining a calculation formula (2).
In the formula, FRiThe total oil consumption, L, of all the working condition points in the ith Bin is represented; FRjThe fuel consumption of the instantaneous operating point is shown, and L/h; t isiIndicating the number of operating points in the ith Bin.
And (4) calculating the accumulated mileage of each working condition point in the Bin, and calculating a formula shown in formula (3).
In the formula, MiThe accumulated mileage km of all the working condition points in the ith Bin is represented; v. ofjThe vehicle speed of the instantaneous working condition point is represented by km/h; t isiIndicating the number of operating points in the ith Bin.
And (4) calculating the average hundred kilometer oil consumption in each Bin according to a calculation formula (4).
In the formula, FCiRepresenting the average hundred kilometer oil consumption of the ith Bin, L/100 km; FRiThe total oil consumption, L, of all the working condition points in the ith Bin is represented; miAnd the accumulated mileage km of all the working condition points in the ith Bin is shown.
And calculating the weighted average fuel consumption per hundred kilometer of the 5min short segment of the vehicle according to the average fuel consumption per hundred kilometer of each Bin and the working condition proportion of the 5min short segment in each Bin, wherein a calculation formula is shown in a formula (5).
In the formula, FSkRepresenting the weighted average hundred kilometer oil consumption of the kth 5min short segment, L/100 km; FCiRepresenting the average hundred kilometer oil consumption of the ith Bin, L/100 km; piThe working condition proportion of the working condition of the short segment of 5min in different Bin is dimensionless;
and step 3: calculating a relative oil consumption factor;
the invention introduces dimensionless parameters and relative oil consumption factors, see formula (6).
In the formula, FkIs a relative oil consumption factor in the kth 5min short segment and is dimensionless; FS (file system)kRepresenting the weighted average hundred kilometer oil consumption of the kth 5min short segment, L/100 km; flimitFor the set oil consumption limit value, the invention refers to the current heavy commercial vehicle fuel consumption limit value standard GB30510-2014, and determines the fuel consumption limit value according to the maximum design total mass (GVM) of the vehicle;
and 4, step 4: diagnosis of high oil consumption fraction;
calculating the relative oil consumption factor of the kth 5min short segment, setting the limit value of the relative oil consumption factor to be 1.0 (statistical empirical value for reference), marking the kth 5min short segment with the relative oil consumption factor exceeding 1.0 as a high emission segment, and marking the segment as FHi。
Further, the step D: the method for extracting the data after real-time diagnosis and high-oil-consumption working condition identification of the oil consumption of the heavy commercial vehicle by using the diagnostic algorithm comprises the following steps of extracting high-oil-consumption segments and synchronous monitoring data stream information, storing the working condition segment data information in a cellular data form, and before numbering, further comprising:
will be marked as FHiThe high-oil-consumption severe working condition segment and the synchronous data flow information thereof are extracted from the original data flow in a data group form.
Further, the step D: the method for extracting the data after real-time diagnosis and high-oil-consumption working condition identification of the oil consumption of the heavy commercial vehicle by using the diagnostic algorithm comprises the following steps of extracting high-oil-consumption segments and synchronous monitoring data stream information, storing the working condition segment data information in a cellular data form, numbering the working condition segment data information, and further comprising the following steps of:
the high oil consumption segments are extracted according to the relative oil consumption factor, and analysis functions such as relevant vehicle working condition analysis and engine working condition analysis can be performed.
The invention also requests to protect a device for dynamically identifying the actual running high-oil-consumption severe working condition of the heavy commercial vehicle, which is characterized by comprising the following steps of: the system comprises a vehicle-mounted terminal on-line monitoring system, a cloud monitoring platform and a database repository, wherein,
the vehicle-mounted terminal online monitoring system is installed at an OBD diagnosis interface of the diesel vehicle and is used for acquiring signals such as the actual running speed of the heavy commercial vehicle, the running state parameters of the diesel engine, the fuel flow of the engine and the like in real time;
the cloud monitoring platform can realize the functions of receiving, diagnosing, extracting working conditions and storing a database of data acquired by the vehicle-mounted terminal on-line monitoring system, receives and uploads the acquired signals of the actual running speed of the heavy commercial vehicle, the running state parameters of the diesel engine, the fuel flow of the engine and the like in real time through the GPRS technology, and further according to a high-oil-consumption severe working condition diagnosis model which is designed in the cloud monitoring platform and is actually operated by the heavy commercial vehicle, real-time diagnosis and high-oil-consumption working condition recognition are carried out on the oil consumption of the heavy commercial vehicle by adopting a diagnosis algorithm, data obtained after the real-time diagnosis and the high-oil-consumption working condition recognition of the oil consumption of the heavy commercial vehicle by adopting the diagnosis algorithm are extracted through the cloud monitoring platform, the extracted high-oil-consumption segments and the synchronous monitoring data flow information are stored in a cellular data form, and the working condition segment data information is numbered.
Preferably, the vehicle-mounted terminal online monitoring system installed on the OBD diagnosis interface of the heavy commercial vehicle acquires the signal requirements of the actual running vehicle speed, the running state parameters of the diesel engine, the fuel flow of the engine and the like of the heavy commercial vehicle in real time, and the signal requirements are as follows: the frequency of the collected data of the vehicle speed is 1 Hz.
The cloud monitoring platform comprises a high-oil-consumption severe working condition diagnosis module and a high-oil-consumption severe working condition extraction module;
the high fuel consumption diagnosis module comprises a diagnosis algorithm;
the designed heavy commercial vehicle actual operation high oil consumption severe working condition diagnosis model in the cloud monitoring platform adopts a diagnosis algorithm to diagnose the oil consumption of the heavy commercial vehicle in real time and recognize the high oil consumption working condition, and the diagnosis algorithm specifically comprises the following steps:
step 1: dividing working conditions;
step 2: calculating the oil consumption of the short working condition segment;
and step 3: calculating a relative oil consumption factor;
and 4, step 4: high oil consumption fraction diagnosis.
The fuel consumption diagnosis algorithm comprises the following steps of 1: and (5) dividing working conditions. The specific power VSP and the instantaneous speed v of the motor vehicle are selected as the characterization parameters of the microscopic running mode of the motor vehicle, and the calculation formula of the VSP is shown in the formula (1).
(3) The diagnostic algorithm, step 2: and calculating the oil consumption of the short working condition segment. Dividing the running working condition and oil consumption data of the vehicle in each 5min short segment into a microscopic running mode Bin corresponding to the v-VSP, calculating the oil consumption of all transient working condition points in each Bin, and obtaining a calculation formula (2). And (3) calculating the accumulated mileage of the working condition points in each Bin, and calculating the average hundred kilometer oil consumption in each Bin, wherein the calculation formula is shown in a formula (4). And calculating the weighted average fuel consumption per hundred kilometer of the 5min short segment of the vehicle according to the average fuel consumption per hundred kilometer of each Bin and the working condition proportion of the 5min short segment in each Bin, wherein a calculation formula is shown in a formula (5).
(4) The diagnostic algorithm, step 3: and calculating the relative oil consumption factor. The invention introduces dimensionless parameters and relative oil consumption factors, and determines the limit value of the fuel consumption according to the maximum design total mass (GVM) of the vehicle by referring to the current limit value standard GB30510-2014 of the fuel consumption of the heavy commercial vehicle.
(5) The diagnostic algorithm, step 4: high oil consumption fraction diagnosis. Calculating the relative oil consumption factor of the kth 5min short segment, setting the limit value of the relative oil consumption factor to be 1.0, marking the kth 5min short segment with the relative oil consumption factor exceeding 1.0 as a high-emission segment, and marking the segment as FHi。
And extracting and storing the high-oil-consumption severe working condition segment marked as FHi and synchronous data flow information thereof in a data form, and realizing calling and high-emission severe working condition segment analysis.
The high oil consumption severe working condition extraction module further comprises:
will be marked as FHiThe high-oil-consumption severe working condition segment and the synchronous data flow information thereof are extracted from the original data flow in a data group form.
The high oil consumption severe working condition extraction module further comprises:
the high oil consumption segments are extracted according to the relative oil consumption factor, and analysis functions such as relevant vehicle working condition analysis and engine working condition analysis can be performed.
The above embodiments are provided only for the purpose of describing the present invention and are not intended to limit the scope of the present invention. The scope of the invention is defined by the appended claims. Various equivalent substitutions and modifications can be made without departing from the spirit and principles of the invention, and are intended to be within the scope of the invention.
Claims (6)
1. A method for dynamically identifying the actual operation high-oil-consumption severe working condition of a heavy commercial vehicle is characterized by comprising the following steps of:
a: the method comprises the steps that a vehicle-mounted terminal online monitoring system is installed on an OBD diagnosis interface of the heavy commercial vehicle, and the actual running speed of the heavy commercial vehicle, the running state parameters of a diesel engine and engine fuel flow signals are collected in real time;
b: the collected data information of the actual running speed of the heavy commercial vehicle, the running state parameters of the diesel engine and the engine fuel flow signal is uploaded to a cloud monitoring platform in real time through a GPRS technology;
c: according to a high-oil-consumption severe working condition diagnosis model which is designed in a cloud monitoring platform and is actually operated by the heavy commercial vehicle, a diagnosis algorithm is adopted to diagnose the oil consumption of the heavy commercial vehicle in real time and identify the high-oil-consumption working condition;
d: the method comprises the steps that a diagnosis algorithm is adopted to carry out real-time diagnosis on oil consumption of the heavy commercial vehicle, data obtained after high oil consumption working condition identification is extracted through a cloud monitoring platform, extracted high oil consumption segments and synchronous monitoring data flow information are stored in a cellular data form, and the data information is numbered;
in the step A, a vehicle-mounted terminal online monitoring system is installed on an OBD diagnosis interface of the heavy commercial vehicle, and the requirements of acquiring the actual running speed of the heavy commercial vehicle, the running state parameters of the diesel engine and the fuel flow signal of the engine in real time are met: the frequency of data acquisition of the vehicle speed is 1 Hz;
and C, according to the high-oil-consumption severe working condition diagnosis model which is designed in the cloud monitoring platform and is actually operated by the heavy commercial vehicle, real-time diagnosis and high-oil-consumption working condition recognition are carried out on the oil consumption of the heavy commercial vehicle by adopting a diagnosis algorithm, and the diagnosis algorithm specifically comprises the following steps:
step 1: working condition division, namely determining a VSP Bin interval of the vehicle according to different running states of the vehicle and instantaneous VSP data;
step 2: calculating the oil consumption of short condition segments, dividing the operation working conditions and the oil consumption data of vehicles in the short segment of every 5min into microcosmic operation modes Bin corresponding to the working condition division regions, and calculating the oil consumption of all transient working condition points in each Bin;
and step 3: calculating a relative oil consumption factor, introducing dimensionless parameters, referring to the current limit value standard GB30510-2014 of the fuel consumption of the heavy commercial vehicle, and determining the limit value of the fuel consumption according to the maximum design total mass of the vehicle;
and 4, step 4: and (4) diagnosing the high oil consumption segment, calculating a relative oil consumption factor of the kth 5min short segment, setting the limit value of the relative oil consumption factor to be 1.0, and marking the kth 5min short segment with the relative oil consumption factor exceeding 1.0 as a high emission segment.
2. The method for dynamically identifying the severe working condition with high fuel consumption in the actual operation of the heavy commercial vehicle as claimed in claim 1, wherein the method comprises the following steps:
the step D: the method for extracting the data after real-time diagnosis and high-oil-consumption working condition identification of the oil consumption of the heavy commercial vehicle by using the diagnostic algorithm comprises the following steps of extracting high-oil-consumption segments and synchronous monitoring data stream information, storing the working condition segment data information in a cellular data form, and before numbering, further comprising:
will be marked as FHiThe high-oil-consumption severe working condition segment and the synchronous data flow information thereof are extracted from the original data flow in a data group form.
3. The method for dynamically identifying the severe working condition with high fuel consumption in the actual operation of the heavy commercial vehicle as claimed in claim 1, wherein the method comprises the following steps:
the step D: the method for extracting the data after real-time diagnosis and high-oil-consumption working condition identification of the oil consumption of the heavy commercial vehicle by using the diagnostic algorithm comprises the following steps of extracting high-oil-consumption segments and synchronous monitoring data stream information, storing the working condition segment data information in a cellular data form, numbering the working condition segment data information, and further comprising the following steps of:
and extracting the high oil consumption segment according to the relative oil consumption factor, and performing related vehicle working condition analysis and engine working condition analysis functions.
4. The utility model provides a device of the abominable operating mode of heavy commercial car actual operation high oil consumption of dynamic identification which characterized in that includes: the system comprises a vehicle-mounted terminal on-line monitoring system, a cloud monitoring platform and a database repository, wherein,
the vehicle-mounted terminal online monitoring system is installed at an OBD diagnosis interface of the diesel vehicle and is used for acquiring the actual running speed of the heavy commercial vehicle, the running state parameters of the diesel engine and the fuel flow signals of the engine in real time;
the cloud monitoring platform can realize the functions of receiving, diagnosing, extracting working conditions and storing a database of the data acquired by the vehicle-mounted terminal on-line monitoring system, receives and uploads the acquired actual running speed of the heavy commercial vehicle, the running state parameters of the diesel engine and the fuel flow signals of the engine in real time through the GPRS technology, the method further comprises the steps of adopting a diagnosis algorithm to carry out real-time diagnosis and high-oil-consumption working condition identification on the oil consumption of the heavy commercial vehicle according to a high-oil-consumption severe working condition diagnosis model which is actually operated by the heavy commercial vehicle and is designed in a cloud monitoring platform, adopting the diagnosis algorithm to carry out real-time diagnosis and high-oil-consumption working condition identification on the oil consumption of the heavy commercial vehicle, and storing the extracted high-oil-consumption segments and synchronous monitoring data flow information in a cellular data form and numbering the working condition segment data information by an extraction method of the cloud monitoring platform;
the on-line monitoring system of the vehicle-mounted terminal installed on the OBD diagnosis interface of the heavy commercial vehicle acquires the vehicle speed, the diesel engine running state parameters and the engine fuel flow signal of the actual running of the heavy commercial vehicle in real time, and the requirements are met: the frequency of data acquisition of the vehicle speed is 1 Hz;
the cloud monitoring platform comprises a high-oil-consumption severe working condition diagnosis module and a high-oil-consumption severe working condition extraction module;
the high fuel consumption diagnosis module comprises a diagnosis algorithm;
the designed heavy commercial vehicle actual operation high oil consumption severe working condition diagnosis model in the cloud monitoring platform adopts a diagnosis algorithm to diagnose the oil consumption of the heavy commercial vehicle in real time and recognize the high oil consumption working condition, and the diagnosis algorithm specifically comprises the following steps:
step 1: working condition division, namely determining a VSP Bin interval of the vehicle according to different running states of the vehicle and instantaneous VSP data;
step 2: calculating the oil consumption of short condition segments, dividing the operation working conditions and the oil consumption data of vehicles in the short segment of every 5min into microcosmic operation modes Bin corresponding to the working condition division regions, and calculating the oil consumption of all transient working condition points in each Bin;
and step 3: calculating a relative oil consumption factor, introducing dimensionless parameters, referring to the current limit value standard GB30510-2014 of the fuel consumption of the heavy commercial vehicle, and determining the limit value of the fuel consumption according to the maximum design total mass of the vehicle;
and 4, step 4: and (4) diagnosing the high oil consumption segment, calculating a relative oil consumption factor of the kth 5min short segment, setting the limit value of the relative oil consumption factor to be 1.0, and marking the kth 5min short segment with the relative oil consumption factor exceeding 1.0 as a high emission segment.
5. The device for dynamically identifying the severe conditions of high fuel consumption in the actual operation of the heavy-duty commercial vehicle according to claim 4, further comprising:
the high oil consumption severe working condition extraction module further comprises:
will be marked as FHiThe high-oil-consumption severe working condition segment and the synchronous data flow information thereof are extracted from the original data flow in a data group form.
6. The device for dynamically identifying the severe conditions of high fuel consumption in the actual operation of the heavy-duty commercial vehicle according to claim 4, further comprising:
the high oil consumption severe working condition extraction module further comprises:
and extracting the high oil consumption segment according to the relative oil consumption factor, and performing related vehicle working condition analysis and engine working condition analysis functions.
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