CN111818487A - Signal transmission optimization method for sensor group of electric vehicle network node - Google Patents
Signal transmission optimization method for sensor group of electric vehicle network node Download PDFInfo
- Publication number
- CN111818487A CN111818487A CN202010368557.6A CN202010368557A CN111818487A CN 111818487 A CN111818487 A CN 111818487A CN 202010368557 A CN202010368557 A CN 202010368557A CN 111818487 A CN111818487 A CN 111818487A
- Authority
- CN
- China
- Prior art keywords
- state
- alarm
- value
- monitoring
- quantities
- 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.)
- Pending
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
- H04W4/48—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P] for in-vehicle communication
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/40—Bus networks
- H04L12/40006—Architecture of a communication node
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/40—Bus networks
- H04L2012/40267—Bus for use in transportation systems
- H04L2012/40273—Bus for use in transportation systems the transportation system being a vehicle
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Small-Scale Networks (AREA)
Abstract
The invention discloses a sensor group signal transmission optimization method of an electric vehicle network node. The process is as follows: setting a plurality of communication signals, detecting the monitoring quantity of each sensor in a sensor group on a network node, determining communication values corresponding to the communication signals according to the monitoring quantities of all the sensors, and taking the communication signals and the corresponding communication values as bus output signals of the sensor group. The invention covers all effective information uploading requirements of the monitoring quantity of the sensor group through a plurality of communication signals, greatly reduces the occupation quantity of bus resources, and has simple method and reasonable design.
Description
Technical Field
The invention belongs to the technical field of automobiles, and particularly relates to a sensor group signal transmission optimization method for an electric automobile network node.
Background
With the advancement of the four deep developments of the electric automobile industry, such as electrification, intellectualization, networking, sharing and the like, the related technologies are gradually mature, the information mastery degree of a single vehicle-mounted network node is higher and higher, and the information mastery degree is represented as follows: the requirement on the state details of each piece of information of the node is more and more, the requirement on the precision of each piece of information of the node is more and more high, and the requirement on the effectiveness of each piece of information of the node is higher; this has led directly to an increasing amount of data being transmitted on the bus by the individual network nodes.
The increase of the data transmission amount of a single node is mainly represented in the following three directions: 1. the number of signals is increasing (including interface signals and internal sensor signals); 2. the signal length is longer and longer (the display precision is improved); 3. the signaling period is shorter and shorter (improving real-time). In the three directions, the increase of the number of signals is the main increasing point of the data transmission amount of the node, wherein the increase of the number of bus signals corresponding to the monitoring amount of the sensor is most prominent, and the increase ratio of the bus signals in a part of nodes (such as BMS) reaches nine times of the increase of the data amount of the whole node.
In other words, an increase in the number of bus signals corresponding to the amount of sensor monitoring is a major cause of a sudden increase in the amount of node bus data. How to optimize these signal designs is the key to reducing the amount of data in the network nodes and reducing the bus load.
At present, the monitoring quantity of sensors in the vehicle-mounted network node of the electric automobile is mainly divided into sensor groups of voltage type, current type, temperature type, rotating speed type, torque type and the like according to types. For example, cell temperature group, cell voltage group in BMS nodes; and an MCU internal temperature group, an MCU internal low-voltage group, an MCU phase current group and the like in the MCU node. The monitoring quantities corresponding to the same group of sensors have the same dimension, even have the same range.
The conventional design idea of the bus signal of each sensor monitoring quantity is as follows: setting a corresponding bus signal for each sensor monitoring quantity on a bus independently, wherein the bus signals corresponding to the sensor monitoring quantities are independent and do not interfere with each other; for example, there are 108 single voltage sensors and 48 temperature sensors in the BMS node of a certain type, and the current design scheme is to directly use a total of 108 independent bus voltage signals and 48 bus temperature signals to represent, and to occupy up to 34 bus message frames in combination with the current precision requirement. There are even thousands of voltage sensors and temperature sensors in BMS node in some car models, and similar examples are many.
The design idea has the advantages that: the specific information change expressing the monitoring quantity of the single sensor can be directly known through a bus signal. The disadvantages are that: when the number of the node sensors is more and more, and the requirements on the information accuracy and the real-time performance of the monitoring quantity are higher and higher, the effective information can be more and more inconvenient to check through corresponding bus signals, and a large amount of bus resources are occupied.
The fundamental reason for this situation is that when the bus signal design is performed on the monitored quantities of each sensor, the system level of the monitored quantity group of sensors is not designed into an integrated manner, but the correlation among the monitored quantities of each sensor is artificially isolated and designed individually. The effective information quantity transmitted by each bus signal is not full, redundant information of each relevant sensor corresponding to the bus signal is very large, and network resource cost occupied by the signal is very much, so that the bus load is further increased.
Therefore, before the subversion technology updating and application of the existing bus structure and communication protocol does not appear, how to effectively utilize the existing limited bus load resources and optimize the bus signal design scheme of the monitoring quantity of the sensor is urgent.
Disclosure of Invention
The invention aims to solve the defects existing in the background technology, and provides a sensor group signal transmission optimization method of an electric vehicle network node, so as to solve the problem that bus resource consumption is continuously aggravated when the signal quantity of a vehicle-mounted single network node is increased too fast.
The technical scheme adopted by the invention is as follows: a plurality of communication signals are set, the monitoring quantity of each sensor in the sensor group on the network node is detected, communication values corresponding to the communication signals are determined according to the monitoring quantities of all the sensors, and the communication signals and the corresponding communication values are used as bus output signals of the sensor group.
Further, the plurality of communication signals include state signals capable of showing the overall real-time change state of all monitoring quantities in the sensor group, and communication values corresponding to the state signals are state values.
Further, the process of determining the state value is:
comparing whether all the monitoring quantities are greater than or equal to zero or less than or equal to zero or greater than zero and less than zero;
if all the monitored quantities are larger than or equal to zero, determining the maximum value in all the monitored quantities as a state value;
if all the monitored quantities are less than or equal to zero, determining the minimum value of all the monitored quantities as a state value;
and if the monitoring quantity which is larger than zero and smaller than zero exists at the same time, determining that the state value is zero.
Further, the plurality of communication signals include alarm signals capable of reflecting the overall abnormal state levels of all monitored quantities in the sensor group, and communication values corresponding to the alarm signals are alarm values.
Further, the process of determining the alarm value is as follows: setting a plurality of alarm thresholds according to the size sequence, forming alarm intervals between adjacent alarm thresholds, wherein each alarm interval corresponds to an alarm level, comparing the size relationship between the state value and each alarm interval, and determining the alarm level corresponding to the alarm interval as the alarm value when the state value falls into a certain alarm interval.
Further, the plurality of communication signals include a fault list signal capable of reflecting name information of all monitoring quantities in the sensor group, and a communication value corresponding to the fault list signal is a fault list value.
Further, the process of determining the fault list values is: in the process of determining the state value and the alarm value, all the monitoring quantities are arranged in a descending order according to the comparison result of the monitoring quantities, the number of the sensor corresponding to each monitoring quantity and the alarm value are recorded, and a list is formed to serve as the fault list value.
Further, after the monitoring quantities of all the sensors are obtained, whether all the monitoring quantities are quantities in the same measuring range or not is judged, if not, the quantities in different measuring ranges are converted into the monitoring quantities in the same measuring range, and a communication value is determined according to the converted monitoring quantities; if yes, determining the communication value according to the original monitoring quantity.
Further, the process of converting the monitored quantities of different range ranges into the quantities of the same range is as follows: setting a plurality of state thresholds according to the size sequence, wherein each state threshold has a one-to-one corresponding alarm threshold, a state interval is formed between adjacent state thresholds, comparing the size relation between the monitoring quantity and each state interval, and when the monitoring quantity falls into a certain state interval, determining the converted monitoring quantity according to the two state thresholds forming the state interval, the corresponding alarm thresholds and the monitoring quantity.
Further, the converted monitoring amount is determined by the following formula
Where η i _ t is the amount monitored after conversion, Xi _ t is the amount monitored before conversion, Xin+1The greater of the two state thresholds of the state interval in which Xi _ t falls, XinThe smaller of the two state thresholds of the state interval in which Xi _ t falls, Xin+1Greater than Xin，Xn+1Is Xin+1Corresponding alarm threshold value, XnIs XinA corresponding alarm threshold.
The invention has the beneficial effects that: 1. the method has the advantages that all effective information uploading requirements of the monitoring quantity of the sensor group are included through a plurality of communication signals, the occupation quantity of bus resources is greatly reduced, the uploading is not distorted, the method is simple, the design is reasonable, and the operation state including whether the running state of the monitoring quantity is normal or not is judged; b. monitoring severity level when quantity is abnormal; c. name of the anomaly monitoring volume; d. the integral variation trend of all monitoring quantities corresponding to the sensor group. 2. The method has strong universality and can be suitable for monitoring quantity of sensor groups of all categories. 3. The optimization strength of the node bus resources depends on the number of sensors and sensor groups in the nodes; the more the sensor monitoring amount is, the better the optimization effect is, and even more than 50% of resources can be saved.
Drawings
FIG. 1 is a schematic diagram of an optimization scheme of the present invention.
FIG. 2 is a flow chart of the calculation of the state value according to the present invention.
FIG. 3 is a flow chart of the alarm value calculation of the present invention.
FIG. 4 is a flow chart of the conversion of the monitoring amount according to the present invention.
Detailed Description
The following further describes embodiments of the present invention with reference to the drawings. It should be noted that the description of the embodiments is provided to help understanding of the present invention, but the present invention is not limited thereto. In addition, the technical features involved in the embodiments of the present invention described below may be combined with each other as long as they do not conflict with each other. Based on the embodiments of the present invention, other embodiments obtained by persons skilled in the art without any creative effort belong to the protection scope of the present invention.
The invention provides a sensor group signal transmission optimization method of an electric vehicle network node, which comprises the steps of setting a plurality of communication signals, detecting the monitoring quantity of each sensor in a sensor group on the network node, determining communication values corresponding to the plurality of communication signals according to the monitoring quantities of all the sensors, taking the plurality of communication signals and the corresponding communication values as output signals of the sensor group, forming a general signal group design scheme of the sensor group, and uploading all effective information of the monitoring quantities of the sensors of the group to a bus in real time.
In the scheme, after the monitoring quantities of all the sensors are acquired, whether all the monitoring quantities are quantities in the same measuring range or not is judged, if not, the quantities in different measuring ranges are converted into the monitoring quantities in the same measuring range, and a communication value is determined according to the converted monitoring quantities; if yes, determining the communication value according to the original monitoring quantity. The process of converting the monitored quantities of different measuring range into the quantities of the same measuring range is as follows: setting a plurality of state thresholds according to the size sequence, wherein each state threshold has a one-to-one corresponding alarm threshold, forming a state interval between adjacent state thresholds, comparing the monitored quantity with the size relation of each state interval, and determining the converted monitored quantity according to the following formulas according to the two state thresholds forming the state interval, the corresponding alarm thresholds and the monitored quantity when the monitored quantity falls into a certain state interval
Where η i _ t is the amount monitored after conversion, Xi _ t is the amount monitored before conversion, Xin+1The greater of the two state thresholds of the state interval in which Xi _ t falls, XinThe smaller of the two state thresholds of the state interval in which Xi _ t falls, Xin+1Greater than Xin，Xn+1Is Xin+1Corresponding alarm threshold value, XnIs XinA corresponding alarm threshold.
n starts to take a value from 0 and increases in sequence according to the number of the state thresholds, namely if 5 state thresholds exist and the maximum value corresponding to n is 4, four state intervals are correspondingly arranged, wherein the maximum value is Xio～Xi1、Xi1～Xi2、Xi2～Xi3、Xi3～Xi4The corresponding alarm intervals are X respectively0～X1、X1～X2、X2～X3、X3～X4And each state threshold value can be a positive value or a negative value and is determined according to actual needs. In this embodiment, 8 state thresholds are set, including four positive thresholds and four negative thresholds, and the sizes of the four state thresholds are in a section symmetry relationship, so as to be linked with the vehicle general fault levels (three fault levels, such as alarm fault nom, derating fault high, and shutdown fault over), and it is easy to understand that the 8 state thresholds may also be in another formIs represented by, e.g. -Xilimit、-Xiover、-Xihigh、-Xinom、Xinom、Xihigh、Xiover、XilimitThe corresponding 8 fault thresholds may also be represented in another form, such as-Xlimit、-Xover、-Xhigh、-Xnom、Xnom、Xhigh、Xover、XlimitNamely, the combination of the positive and negative intervals forms 7 state intervals, and a 7-segment alarm mechanism.
The above-mentioned interval when η i _ t falls is Xi1～Xi2When the temperature of the water is higher than the set temperature,
in the above solution, the plurality of communication signals include a state signal capable of reflecting the whole real-time variation trend of all monitored quantities in the sensor group, the communication value corresponding to the state signal is a state value, that is, the whole real-time value of all monitored quantities of the whole sensor group is displayed on the bus, and the process of determining the state value is as follows:
comparing whether all the monitoring quantities are greater than or equal to zero or less than or equal to zero or greater than zero and less than zero;
if all the monitored quantities are larger than or equal to zero, determining the maximum value in all the monitored quantities as a state value;
if all the monitored quantities are less than or equal to zero, determining the minimum value of all the monitored quantities as a state value;
and if the monitoring quantity which is larger than zero and smaller than zero exists at the same time, determining that the state value is zero.
In the above scheme, the plurality of communication signals include an alarm signal capable of indicating the overall abnormal state level of all monitored quantities in the sensor group, and the communication value corresponding to the alarm signal is an alarm value to monitor whether the monitored quantities of the group are normal or not and the severity of the monitored quantities in abnormal operation, that is, when any monitored quantity in the sensor group is abnormal, the communication value corresponding to the alarm signal reports the abnormal monitored quantity of the sensor group to the bus and further indicates the fault level information of the monitored quantity of the group. The process of determining the alarm value is as follows: push buttonSetting a plurality of alarm thresholds according to the sequence of magnitude, forming an alarm interval between adjacent alarm thresholds, in this embodiment, the alarm thresholds are respectively-X described abovelimit、-Xover、-Xhigh、-Xnom、Xnom、Xhigh、Xover、XlimitIn this embodiment, the alarm levels of the symmetric intervals are set to be the same according to the positive and negative symmetric threshold relationship, and then the 7 alarm intervals correspond to 4 alarm levels, which are respectively 0X0, 0X1, 0X2 and 0X3, that is, the interval-X is the interval-Xnom～XnomIs in a scale of 0X0, interval-Xhigh～-XnomAnd interval Xnom～XhighIs equally ranked as 0X1, interval-Xover～-XhighAnd interval Xhigh～XoverIs equally ranked as 0X2, interval-Xlimit～-XoverAnd interval Xover～XlimitThe same level of the alarm interval is 0x3, only the magnitude relation between the absolute value of the state value and each alarm interval is compared at the moment, and when the state value falls into a certain alarm interval, the alarm level corresponding to the alarm interval is determined to be the alarm value.
In the above scheme, the plurality of communication signals include a fault list signal capable of reflecting name information of all monitored quantities in the sensor group, a communication value corresponding to the fault list signal is a fault list value, and a list of abnormal monitored quantities in all monitored quantities corresponding to the sensor group is explicitly reported. The process of determining the fault list values is: in the process of determining the state value and the alarm value, all the monitoring quantities are arranged in a descending order according to the comparison result of the monitoring quantities, the number of the sensor corresponding to each monitoring quantity and the alarm value are recorded, and a list is formed to serve as the fault list value.
Example 1:
as shown in fig. 1, the ECU node includes at least one sensor group X, which is formed by m sensors (sensors in the same dimension), and the numbers of the sensors are respectively denoted as X1, X2. According to the signal group design method, three communication signals are designed on a bus in total and used for uploading the group of information characteristic quantities, namely, a state signal, an alarm signal and a fault list signal, and the value names of the sizes of the signals are respectively a state value GroupX _ Valle, an alarm value GroupX _ AlarmLevel and a fault list value GroupX _ Absormal VariableList.
Each communication signal has the following characteristics:
setting threshold values and value ranges of the state signals and the alarm signals: according to the classification principle of general fault grades (three fault grades such as alarm fault, derating fault, shutdown fault and the like) of the automobile,
the state signal of the sensor group is provided with 8 state thresholds in total, namely warning thresholds +/-Xi, in positive and negative directions on the basis of zero point correspondencenomDerating threshold + -XihighTurn-off threshold. + -. XioverLimiting value. + -. XilimitThe value range is symmetrically divided into 7 sections. The state signal of the sensor group is correspondingly set with 8 alarm thresholds (warning threshold +/-X) in total in positive and negative directions based on zeronomDerating threshold + -XhighTurn-off threshold ± XoverExtreme value. + -. Xlimit) The value range is symmetrically divided into 7 sections. And each alarm threshold point of the monitoring quantity Xi and the state threshold point of the sensor group are in one-to-one mapping relation.
Designing a value range of a fault list signal: and displaying the list of abnormal monitoring quantity in sequence from high to low according to the state signal value, and only displaying the monitoring quantity list with the highest severity grade when the monitoring quantity of the sensor group is abnormal.
The calculation and the update of each communication value are carried out according to the following steps:
step1, after the ECU is powered on, acquiring each monitored quantity X1_ t, X2_ t, at the time t of the sensor group X.
Step2, unifying the range of each monitored quantity, and converting each monitored quantity into the quantity in the same range.
If each sensor is a sensor with the same measuring range, the condition signal follows the dimension unit, and the monitored quantity X1_ t, X2_ t, X i _ t, Xi _ t, X.
If the range of each sensor is not completely the same, the option2.2 converts each sensor monitoring quantity value X1_ t, X2_ t,. once.., Xi _ t,. once.. at time t, Xm _ t into a percentage value η 1_ t, η 2_ t,. once.. eta.i _ t,. once.. eta.m _ t according to the monitoring quantity value percentage conversion model in fig. 4, and only the conversion flow of the positive threshold interval is shown in fig. 4, and the conversion process of the negative threshold interval is similar and will not be described in detail here. Then, the percentage value of the status signals of the sensor group is obtained by calculation according to the status value calculation flow in fig. 2, and the status value is a dimensionless percentage numerical value (i.e., converted quantity).
Step3, calculating the real-time state value of the monitoring amount group according to the state value calculation flow of the monitoring amount group in fig. 2.
At the time t, if the monitoring quantity measuring range is the same, then:
when all monitoring quantities are greater than or equal to zero, obtaining the state Value of the sensor group as GroupX _ Value _ t ═ max { X1_ t, X2_ t,. once.. Xm _ t };
when all monitoring quantities are less than or equal to zero, obtaining a sensor group state signal Value of min { X1_ t, X2_ t,. once.. Xm _ t };
if the monitoring quantity measuring range is different, then:
when all the monitored quantities are greater than or equal to zero, obtaining a sensor group state signal Value of max { η 1_ t, η 2_ t,. eta.m _ t };
when all the monitored quantities are less than or equal to zero, obtaining a sensor group state signal Value of min { η 1_ t, η 2_ t,. eta.m _ t };
whether the measurement ranges are the same or not, if all the monitoring amounts exist more than zero and less than zero at the same time, determining that the group _ Value _ t is 0.
Step4, updating the alarm signal and the fault list signal according to the state value of the monitoring quantity group at the time t and the flow of fig. 3, wherein the intervals are in positive and negative symmetry, and the alarm levels of the symmetric intervals are the same, so that the comparison of the intervals where the absolute values are located in fig. 3 is taken as the standard, and the alarm value group x _ alarm level of the alarm signal is calculated as follows: determining an alarm interval in which the state value is positioned,
when | GroupX _ value _ t | < XnomIf the value is 0x0, the value is the first level;
when X is presentnom≤|GroupX_Vaule_t|＜XhighIf the value is 0x1, the value is the second level;
when X is presenthigh≤|GroupX_Vaule_t|＜XoverThe GroupX _ AlarmLevel is 0x2, which is the third level;
when X is presentover≤|GroupX_Vaule_t|≤XlimitThe GroupX _ AlarmLevel is 0x3, which is the fourth level;
the calculation method of the fault list value group _ abstract variable list of the fault list signal at time t is as follows:
when GroupX _ AlarmLevel is 0x0, the sensor group fault list value GroupX _ abnormalvriablelist is 0x0, i.e., no fault condition by default.
When the GroupX _ AlarmLevel is more than or equal to 0x1, the signal only displays the monitoring quantity list with the highest severity level, and the monitoring quantity list is displayed in sequence according to the size of the monitoring quantity value.
And Step5, selecting the monitoring quantity to be checked in the fault list according to the fault troubleshooting requirement, and calling and monitoring in the diagnostic instrument.
Through the steps, the effect of uploading the effective information of the sensor group in real time can be achieved.
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present invention are included in the scope of the present invention. Those not described in detail in this specification are within the skill of the art.
Claims (10)
1. A sensor group signal transmission optimization method of an electric vehicle network node is characterized by comprising the following steps: setting a plurality of communication signals, detecting the monitoring quantity of each sensor in a sensor group on a network node, determining communication values corresponding to the communication signals according to the monitoring quantities of all the sensors, and taking the communication signals and the corresponding communication values as bus output signals of the sensor group.
2. The sensor group signal transmission optimization method of the electric vehicle network node according to claim 1, characterized in that: the plurality of communication signals comprise state signals capable of reflecting the overall real-time change state of all monitoring quantities in the sensor group, and communication values corresponding to the state signals are state values.
3. The sensor group signal transmission optimization method of the electric vehicle network node according to claim 2, characterized in that: the process of determining the state value is:
comparing whether all the monitoring quantities are greater than or equal to zero or less than or equal to zero or greater than zero and less than zero;
if all the monitored quantities are larger than or equal to zero, determining the maximum value in all the monitored quantities as a state value;
if all the monitored quantities are less than or equal to zero, determining the minimum value of all the monitored quantities as a state value;
and if the monitoring quantity which is larger than zero and smaller than zero exists at the same time, determining that the state value is zero.
4. The sensor group signal transmission optimization method of the electric vehicle network node according to claim 3, characterized in that: the plurality of communication signals comprise alarm signals capable of reflecting the overall abnormal state grade of all monitored quantities in the sensor group, and communication values corresponding to the alarm signals are alarm values.
5. The sensor group signal transmission optimization method of the electric vehicle network node according to claim 4, characterized in that: the process of determining the alarm value is as follows: setting a plurality of alarm thresholds according to the size sequence, forming alarm intervals between adjacent alarm thresholds, wherein each alarm interval corresponds to an alarm level, comparing the size relationship between the state value and each alarm interval, and determining the alarm level corresponding to the alarm interval as the alarm value when the state value falls into a certain alarm interval.
6. The sensor group signal transmission optimization method of the electric vehicle network node according to claim 5, characterized in that: the communication signals comprise fault list signals capable of reflecting name information of all monitoring quantities in the sensor group, and communication values corresponding to the fault list signals are fault list values.
7. The sensor group signal transmission optimization method of the electric vehicle network node according to claim 6, characterized in that: the process of determining the fault list values is: in the process of determining the state value and the alarm value, all the monitoring quantities are arranged in a descending order according to the comparison result of the monitoring quantities, the number of the sensor corresponding to each monitoring quantity and the alarm value are recorded, and a list is formed to serve as the fault list value.
8. The sensor group signal transmission optimization method of the electric vehicle network node according to claim 1, characterized in that: after acquiring the monitoring quantities of all the sensors, judging whether all the monitoring quantities are quantities in the same measuring range or not, if not, converting the quantities in different measuring ranges into the monitoring quantities in the same measuring range, and determining a communication value according to the converted monitoring quantities; if yes, determining the communication value according to the original monitoring quantity.
9. The sensor group signal transmission optimization method of the electric vehicle network node according to claim 7, characterized in that: the process of converting the monitored quantities of different measuring range into the quantities of the same measuring range is as follows: setting a plurality of state thresholds according to the size sequence, wherein each state threshold has a one-to-one corresponding alarm threshold, a state interval is formed between adjacent state thresholds, comparing the size relation between the monitoring quantity and each state interval, and when the monitoring quantity falls into a certain state interval, determining the converted monitoring quantity according to the two state thresholds forming the state interval, the corresponding alarm thresholds and the monitoring quantity.
10. The sensor group signal transmission optimization method of the electric vehicle network node according to claim 9, characterized in that: the converted monitoring amount is determined by the following formula
Where η i _ t is the amount monitored after conversion, Xi _ t is the amount monitored before conversion, Xin+1The greater of the two state thresholds of the state interval in which Xi _ t falls, XinThe smaller of the two state thresholds of the state interval in which Xi _ t falls, Xin+1Greater than Xin，Xn+1Is Xin+1Corresponding alarm threshold value, XnIs XinA corresponding alarm threshold.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010368557.6A CN111818487A (en) | 2020-05-01 | 2020-05-01 | Signal transmission optimization method for sensor group of electric vehicle network node |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010368557.6A CN111818487A (en) | 2020-05-01 | 2020-05-01 | Signal transmission optimization method for sensor group of electric vehicle network node |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111818487A true CN111818487A (en) | 2020-10-23 |
Family
ID=72848077
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010368557.6A Pending CN111818487A (en) | 2020-05-01 | 2020-05-01 | Signal transmission optimization method for sensor group of electric vehicle network node |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111818487A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113484655A (en) * | 2021-09-07 | 2021-10-08 | 西安热工研究院有限公司 | Redundant measurement line-crossing detection method, system and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002099972A (en) * | 2000-09-26 | 2002-04-05 | Nisshin Kiko Kk | Sensor system |
| CN102192927A (en) * | 2010-11-05 | 2011-09-21 | 重庆大学 | Air-quality monitoring system based on electronic nose technique, and monitoring method thereof |
| CN104678850A (en) * | 2015-01-29 | 2015-06-03 | 深圳一智信息技术有限公司 | Method for intelligent autodiagnosis of vehicle-mounted communication equipment |
| CN109709379A (en) * | 2018-12-11 | 2019-05-03 | 河南辉煌科技股份有限公司 | A kind of track circuit alarm limits method of adjustment based on big data |
| CN110866558A (en) * | 2019-11-13 | 2020-03-06 | 湖南纬拓信息科技有限公司 | Multi-source data fusion analysis-based rotating equipment state early warning method |
-
2020
- 2020-05-01 CN CN202010368557.6A patent/CN111818487A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002099972A (en) * | 2000-09-26 | 2002-04-05 | Nisshin Kiko Kk | Sensor system |
| CN102192927A (en) * | 2010-11-05 | 2011-09-21 | 重庆大学 | Air-quality monitoring system based on electronic nose technique, and monitoring method thereof |
| CN104678850A (en) * | 2015-01-29 | 2015-06-03 | 深圳一智信息技术有限公司 | Method for intelligent autodiagnosis of vehicle-mounted communication equipment |
| CN109709379A (en) * | 2018-12-11 | 2019-05-03 | 河南辉煌科技股份有限公司 | A kind of track circuit alarm limits method of adjustment based on big data |
| CN110866558A (en) * | 2019-11-13 | 2020-03-06 | 湖南纬拓信息科技有限公司 | Multi-source data fusion analysis-based rotating equipment state early warning method |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113484655A (en) * | 2021-09-07 | 2021-10-08 | 西安热工研究院有限公司 | Redundant measurement line-crossing detection method, system and storage medium |
| CN113484655B (en) * | 2021-09-07 | 2022-01-25 | 西安热工研究院有限公司 | Redundant measurement line-crossing detection method, system and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110126841B (en) | Pure electric vehicle energy consumption model prediction method based on road information and driving style | |
| CN106295888B (en) | Method for determining shared time window of public building parking lot configuration based on measured data | |
| CN107798876A (en) | Road traffic exception congestion determination methods based on event | |
| CN103617568A (en) | Setting method for abnormal data determination threshold in steady-state power quality early-warning mechanism | |
| CN114977483B (en) | Fault diagnosis system for intelligent power grid regulation control equipment | |
| CN111818487A (en) | Signal transmission optimization method for sensor group of electric vehicle network node | |
| CN104506137A (en) | Equipment fault diagnosis method and apparatus | |
| CN114801751A (en) | Automobile battery fault prediction system based on data analysis | |
| WO2024050959A1 (en) | Mobile battery state detection device, system, and method | |
| CN101551940A (en) | Urban high-speed road traffic state judging and issuing system and method thereof | |
| CN112782614A (en) | Fault early warning method and device of converter based on multi-information fusion | |
| CN112991096A (en) | Monitoring and managing device and method for configuration type bridge cluster structure | |
| CN108537914A (en) | public bicycle fault diagnosis method | |
| CN113297033A (en) | Vehicle electric control system health assessment method and system based on cloud monitoring data | |
| CN112782499B (en) | Multi-information fusion-based converter state evaluation method and device | |
| CN116842811A (en) | Workshop production line energy consumption analysis method and device based on digital twin and storage medium | |
| CN115561658B (en) | Power battery abnormal cell monitoring method based on data slicing | |
| CN114035056A (en) | Power battery performance detection method, device and equipment | |
| CN109546966A (en) | A kind of the hot spot diagnostic method and device of photovoltaic module | |
| CN104749530B (en) | A kind of electrokinetic cell discharges from power consumption Performance Decay evaluation method and device | |
| CN111696350B (en) | Electric bus local working condition evaluation method based on operation monitoring data | |
| CN114429240A (en) | Method and device for monitoring running state of highway equipment | |
| CN114662304A (en) | Dynamic event trigger filtering estimation method for urban road traffic flow | |
| WO2019187524A1 (en) | Generator unit relocation calculation device and calculation processing method | |
| CN111898895A (en) | Vehicle quality evaluation method and system based on big data fusion |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20201023 |
|
| RJ01 | Rejection of invention patent application after publication |