CN106650963A - Electric car charging equipment detection and maintenance managing method and device - Google Patents
Electric car charging equipment detection and maintenance managing method and device Download PDFInfo
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Abstract
The invention provides an electric car charging equipment detection and maintenance managing method and device. A detection and maintenance plan of each target charging equipment is correspondingly regulated according to the current state of the target charging equipment; and for each target charging equipment in a current failed state, a maintenance scheme corresponding to the target charging equipment is obtained through a maintenance knowledge base according to current operation information of the target charging equipment. By inspecting or maintaining the charging equipment in the abnormal state in time, the failure generation probability of the equipment is decreased, and the equipment utilization rate is increased.
Description
Technical field
The present invention relates to charging equipment of electric automobile field, more particularly, it relates to a kind of inspection of charging equipment of electric automobile
Survey maintenance management method and apparatus.
Background technology
At present, the development that country has put into effect multinomial preferential policy to stimulate and help ev industry, but charge
Problem remains the key factor of restriction Development of Electric Vehicles, by electric automobile itself charge capacity, charging interval, scope of activities
Etc. the impact of reason, the construction of charging equipment starts from the large-scale charging station concentrated to scattered discrete charging pile, small-sized charging
The form conversion stood, and start to explore 5 kilometers of circles that charge, 10 kilometers of types of service such as circle, highway charge point that charge, radiation
Scope is increasing, greatly extends the zone of action of electric automobile, eliminates the electricity anxiety of user, promotes electric automobile
Popularization.
But, traditional charging equipment of electric automobile regular visit mode, because by geographical position, operation maintenance personnel, time etc.
Multiple resources are limited, and cause equipment fault, defect to solve in time, affect charging electric vehicle, waste social resources.
The content of the invention
In view of this, the present invention proposes a kind of charging equipment of electric automobile Automotive maintenance and diagnosis management method and apparatus, is intended to realize
The probability of device fails is reduced, the utilization rate purpose of equipment is improved.
To achieve these goals, it is proposed that scheme it is as follows：
A kind of charging equipment of electric automobile Automotive maintenance and diagnosis management method, including：
Obtain the current operational information of all target charging equipments；
For target charging equipment each described, according to its current operational information, using the state evaluation mould of charging equipment
Type, obtains its current state, and the state includes normal, early warning, warning and failure；
For target charging equipment each described, its repair schedule is adjusted accordingly according to its current state；
For each described target charging equipment that current state is failure, according to its current operational information, using maintenance
Knowledge base obtains corresponding maintenance program.
Preferably, described for target charging equipment each described, according to its current operational information, using charging equipment
State evaluation model, after obtaining its current state, also include：
For each described target charging equipment that current state is normal, early warning or warning, letter is currently run according to it
Breath, using the deterioration analysis model of charging equipment, predicts its moment broken down；
According to the corresponding fault message of each described target charging equipment, Parts Inventory Managed Solution is generated.
Preferably, before the current operational information for obtaining all target charging equipments, also include：
Sample data is analyzed using decision Tree algorithms, obtains the deterioration analysis model of the charging equipment.
Preferably, before the current operational information for obtaining all target charging equipments, also include：
Sample data is analyzed using decision Tree algorithms, obtains the state evaluation model of the charging equipment.
A kind of charging equipment of electric automobile Automotive maintenance and diagnosis management device, including：
Information acquisition unit, for obtaining the current operational information of all target charging equipments；
State evaluation unit, for for each described target charging equipment, according to its current operational information, using charging
The state evaluation model of equipment, obtains its current state, and the state includes normal, early warning, warning and failure；
Plan rescheduling unit, for for each described target charging equipment, according to its current state to its repair schedule
Adjust accordingly；
Maintenance program unit, it is current according to its for for each described target charging equipment that current state is failure
Operation information, using Knowledge of Maintenance storehouse corresponding maintenance program is obtained.
Preferably, described device, also includes：
Failure predication unit, for for each described target charging equipment that current state is normal, early warning or warning,
According to its current operational information, using the deterioration analysis model of charging equipment, its moment broken down is predicted；
Stock-keeping unit, for according to the corresponding fault message of each described target charging equipment, generating Parts Inventory
Managed Solution.
Preferably, described device, also includes：
Forecast model unit, for being analyzed to sample data using decision Tree algorithms, is obtained the charging and is set
Standby deterioration analysis model.
Preferably, described device, also includes：
State model unit, for being analyzed to sample data using decision Tree algorithms, is obtained the charging and is set
Standby state evaluation model.
Compared with prior art, technical scheme has advantages below：
The charging equipment of electric automobile Automotive maintenance and diagnosis management method and apparatus that above-mentioned technical proposal is provided, for described in each
Target charging equipment, adjusts accordingly according to its current state to its repair schedule；And it is every for failure for current state
The individual target charging equipment, according to its current operational information, using Knowledge of Maintenance storehouse corresponding maintenance program is obtained.It is right
In the charging equipment of abnormal condition, patrolled and examined in time or keeped in repair, and then reduced the probability of device fails, raising is set
Standby utilization rate.
Description of the drawings
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
The accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, can be with
Other accompanying drawings are obtained according to these accompanying drawings.
Fig. 1 is the flow chart of charging equipment of electric automobile Automotive maintenance and diagnosis management method provided in an embodiment of the present invention；
Fig. 2 is the flow process of another kind of charging equipment of electric automobile Automotive maintenance and diagnosis management method provided in an embodiment of the present invention
Figure；
Fig. 3 is a kind of schematic diagram of charging equipment of electric automobile Automotive maintenance and diagnosis management device provided in an embodiment of the present invention；
Fig. 4 is the signal of another kind of charging equipment of electric automobile Automotive maintenance and diagnosis management device provided in an embodiment of the present invention
Figure.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than the embodiment of whole.It is based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of creative work is not made
Embodiment, belongs to the scope of protection of the invention.
A kind of charging equipment of electric automobile Automotive maintenance and diagnosis management method is embodiments provided, referring to described in Fig. 1, is somebody's turn to do
Method includes：
Step S11：Obtain the current operational information of all target charging equipments；
Target charging equipment is the charging equipment for needing and monitoring set in advance.Operation information includes but is not limited to following
One or more：Current data, voltage data, alarm data, charged state data, charging equipment interact number with electric automobile
Interaction data according to, charging equipment and mobile terminal or server etc..
Step S12：For target charging equipment each described, according to its current operational information, using the shape of charging equipment
State evaluation model, obtains its current state, and the state includes normal, early warning, warning and failure.
Step S13：For target charging equipment each described, its repair schedule is accordingly adjusted according to its current state
It is whole；
If the current state of target charging equipment is normal, the repair schedule of the target charging equipment is not adjusted
It is whole, i.e., normal polling period and content are performed to the target charging equipment, do not adjust；If the current shape of target charging equipment
State is early warning, then patrol and examine mark emphatically according to what early warning content added corresponding component in content is patrolled and examined；If target charges set
Standby current state is warning, then formulate ad hoc inspection and repair plan to the target charging equipment, is overhauled in advance, and according to alarm
Content add in content is patrolled and examined to corresponding component re-detection mark, using Knowledge of Maintenance storehouse generate breakdown maintenance scheme；
If the current state of target charging equipment is failure, ad hoc inspection and repair plan is formulated to the target charging equipment, immediately to it
Overhauled, and according to defect content add in content is patrolled and examined corresponding component re-detection mark, and formulate corresponding spare part
Outbound list, remind maintainer to carry corresponding spare part and set out scene.
Normally patrol and examine and triggered by timing patrol task, once formulate after periodically perform, have the fixed execution time and
Executor, testing equipment scope, detection project etc..Repair schedule formulate after be assigned to corresponding executor, with the specified time,
The equipment specified and content.Patrol and examine registration after end and patrol and examine result, the detection that result compares state evaluation model is patrolled and examined by this
As a result, state evaluation model is modified.
Step S14：For each described target charging equipment that current state is failure, according to its current operational information,
Corresponding maintenance program is obtained using Knowledge of Maintenance storehouse.
With reference to the rule in Knowledge of Maintenance storehouse, using FST (Finite State Transducer) algorithm to Knowledge of Maintenance storehouse
Enter line retrieval and obtain corresponding maintenance program.Knowledge of Maintenance storehouse, a series of rule for mainly being formed according to expertise and experience
Then.Knowledge of Maintenance stock puts various rules and conclusion, realizes the functions such as storage, the management of maintenance program.Knowledge of Maintenance storehouse is more
New mechanism is that the new problem that will be continuously emerged in practice is added in Knowledge of Maintenance storehouse after summary, by the side of data mining
Method and expert instruct the Dynamic Maintenance of the mode implementation rule for combining.For example, if scene finds that maintenance program is wrong,
After returning maintenance program is modified and is recorded, Knowledge of Maintenance storehouse is modified.
The charging equipment of electric automobile Automotive maintenance and diagnosis management method that the present embodiment is provided, charges for target each described and sets
It is standby, its repair schedule is adjusted accordingly according to its current state；And for current state for failure each described target
Charging equipment, according to its current operational information, using Knowledge of Maintenance storehouse corresponding maintenance program is obtained.To in improper
The charging equipment of state, is patrolled and examined in time or is keeped in repair, and then reduces the probability of device fails, improves the utilization of equipment
Rate.
Before the current operational information for obtaining all target charging equipments, also include：Using decision Tree algorithms to sample number
According to being analyzed, the state evaluation model of charging equipment is obtained.The learning process of specific state evaluation model is as follows：
Prepare the sample data under various states, described sample data item includes operational factor and the outside of charging equipment
Ambient parameter, wherein operational factor include but is not limited to following one or more：Output voltage, output current, auxiliary output
Electric current, auxiliary output voltage, active power, reactive power, temperature, battery input battery, battery input voltage, battery temperature
Include following one or more Deng, external environment condition parameter：Temperature, humidity, wind-force, wind direction, rainfall, immersion, air quality
(travel fatigue quantity of PM10 and the above) etc..
The running status of charging equipment has starting state, precharging state, charged state, its deflated state, halted state, standby
State, off-mode；The malfunction of charging equipment has over-current state, overvoltage condition, over-temperature condition, overcharging state, Wu Fating
Only charged state etc..The operational factor of collection and every kind of running status and malfunction is used as sample data.The number of every kind of state
According to being not less than 100 groups.Data as preparing two parts, it is a as training data, it is a as checking data.
One group data=[output voltage, output current, auxiliary output current, auxiliary output voltage, active power is idle
Power, temperature, battery input battery, battery input voltage, battery temperature, etc., ' charge normal ']
One group data=[output voltage, output current, auxiliary output current, auxiliary output voltage, active power is idle
Power, temperature, battery input battery, battery input voltage, battery temperature, etc., ' over-current state ']
One group data=[output voltage, output current, auxiliary output current, auxiliary output voltage, active power is idle
Power, temperature, battery input battery, battery input voltage, battery temperature, etc., ' overvoltage condition ']
One group data=[output voltage, output current, auxiliary output current, auxiliary output voltage, active power is idle
Power, temperature, battery input battery, battery input voltage, battery temperature, etc., ' overcharging state ']
One group data=[output voltage, output current, auxiliary output current, auxiliary output voltage, active power is idle
Power, temperature, battery input battery, battery input voltage, battery temperature, etc., ' over-temperature condition ']
…………
Data normalization process is carried out to sample data.For example：
Calculate average X of the output voltage in all sample datas：(output voltage values in output voltage values 1+ groups 2 in group 1
Output voltage values n)/n in output voltage values 3+ ...+group n in 2+ groups 3
Calculate the standard variance of the output voltage in all sample datas：(| magnitude of voltage 1- averages X |+| magnitude of voltage 2- averages
|+| magnitude of voltage 3- averages X |+...+| magnitude of voltage n- averages X |) evolution after/n.
Calculate the corresponding characterizing magnitudes of sample data：(magnitude of voltage-average X)/standard variance+0.1
Each numerical value (not including running status amount) in sample is calculated successively, sample characteristics quantity set D is obtained.
Using sample characteristics quantity set D as training tuple decision-tree model is produced as state evaluation model.Detailed process
It is as follows：
(1) a node N is created.
(2) if the tuple in D is all in same class C, then and return N as leaf node, and with C flag it
(3) if candidate attribute collection is sky, N is returned as leaf node, be labeled as many several classes ofs of D, the establishment of the attribute
Terminate.
(4) concentrate from the candidate attribute of D and find out best split criterion, be divided into suitable split point and Split Attribute.
(5) node N is marked using split criterion.
(6) if all centrifugal pumps of the value for being marked as the subset of the Split Attribute, each value for the attribute is set up
One branch, and marked with the value.This Split Attribute is deleted simultaneously.
(7) Split Attribute of optimum is picked out, tuple is divided according to the split point of the attribute and each subregion is produced
Subtree.Using all data tuple set for meeting split point requirement in D as a subregion, if this subregion is sky, plus
One leaf is to node N, many several classes ofs being labeled as in D；If subregion is not sky, plus one (is made by the subtree of the partition creating
Repeat second step to the process of the 8th step for node) arrive node N.
Using checking data as input evaluation of running status model, statistical model output result and state in checking data
The inconsistent quantity of amount, obtains variance rate, if variance rate is in the accurate of 1% model described above with quantity divided by total quantity
Degree is relatively low.If the degree of accuracy is too low, needing to reformulate split criterion carries out modeling rendering.Repetition training and verification process, and
Calculate and check variance rate.
If multipass modification come the variance rate that obtains of re -training it is still very high if, it is necessary to collect training again
Sample set and checking sample, increase the scope for spreading all over of training sample set, it is ensured that parameter is extensive enough, increase enough unusual
Value.Repeat the process for training with verification process, changing collecting sample, modification spreading coefficient, until variance rate is less than 1%.Most
The model for meeting variance rate standard for obtaining eventually is the state evaluation model of the model device.
During use state evaluation model carries out corresponding charging equipment state evaluation, if output result and reality
Running status mismatches or cannot evaluate the situation of state to be occurred, then show that the state evaluation model needs to update.With new acquisition
Service data carry out corrigendum training to state evaluation model, obtain new state evaluation model.
The present embodiment provides another kind of charging equipment of electric automobile Automotive maintenance and diagnosis management method, further solves Parts Inventory
Unreasonable allocation, does not reach the problem of resource optimal allocation.Referring to described in Fig. 2, wherein step S21, S22, S23, S24 respectively with
Step S11, S12, S13, S14 are identical, and the method includes：
Step S21：Obtain the current operational information of all target charging equipments；
Step S22：For target charging equipment each described, according to its current operational information, using the shape of charging equipment
State evaluation model, obtains its current state, and the state includes normal, early warning, warning and failure.
Step S23：For target charging equipment each described, its repair schedule is accordingly adjusted according to its current state
It is whole；
Step S24：For each described target charging equipment that current state is failure, according to its current operational information,
Corresponding maintenance program is obtained using Knowledge of Maintenance storehouse；
Step S25：For each described target charging equipment that current state is normal, early warning or warning, worked as according to it
Front operation information, using the deterioration analysis model of charging equipment, predicts its moment broken down；
The operation information history of forming database of collection target charging equipment, using decision Tree algorithms from being subordinate in database
Relevant information is excavated, the degradation trend change of charging equipment is analyzed, equipment degradation trend model (i.e. inference machine) is derived.Using certainly
The inference strategy of plan tree algorithm is Modus ponens logic rules, the fact that go out new by regular and known facts inference.
Step S26：According to the corresponding fault message of each described target charging equipment, Parts Inventory Managed Solution is generated.
The stockpile number for adjusting charging equipment correspondence spare part is needed after the completion of failure predication, for example, for current state is
The target charging equipment of normal and early warning, then the procurement cycle to the target charging equipment and buying content do not adjust；For
Current state is the target charging equipment of warning, then increase the portion of buying respective numbers according to 70% probability according to warning content
Part, such as the target charging equipment that a certain part has warning is 10, then increase the part of buying 10*70%；It is right
It is the target charging equipment of failure in current state, then buying respective numbers is increased according to 90% probability according to defect content
Part.If the part needed in the repair schedule formulated number in warehouse is 0 or less than safety value, interim buying meter is formulated
Draw, and the procurement cycle of the corresponding component stored in reduction system.
Before the current operational information for obtaining all target charging equipments, also include：Using decision Tree algorithms to sample
Notebook data is analyzed, and obtains the deterioration analysis model of the charging equipment.The learning process of specific deterioration analysis model is same
The learning process of state evaluation model is similar to, and difference is that training data is different, and the training data of deterioration analysis model is necessary
It is at least continuous two-by-two in time, and second group of equipment state and first group are differed in continuous data two-by-two.Make
With the service data of first group of data and the equipment state of second group of data as the input of training data, mould is set up and improved
Type.
For aforesaid each method embodiment, in order to be briefly described, therefore it is all expressed as a series of combination of actions, but
It is that those skilled in the art should know, the present invention is not limited by described sequence of movement, because according to the present invention, certain
A little steps can adopt other orders or while carry out.
It is following for apparatus of the present invention embodiment, can be used for performing the inventive method embodiment.For apparatus of the present invention reality
The details not disclosed in example is applied, the inventive method embodiment is refer to.
The embodiment of the present invention provides a kind of charging equipment of electric automobile Automotive maintenance and diagnosis management device, shown in Figure 3, the dress
Put including：
Information acquisition unit 11, for obtaining the current operational information of all target charging equipments；
State evaluation unit 12, for for each described target charging equipment, according to its current operational information, using filling
The state evaluation model of electric equipment, obtains its current state, and the state includes normal, early warning, warning and failure；
Plan rescheduling unit 13, for for each described target charging equipment, meter being overhauled to it according to its current state
Draw and adjust accordingly；
Maintenance program unit 14, for being each described target charging equipment of failure for current state, works as according to it
Front operation information, using Knowledge of Maintenance storehouse corresponding maintenance program is obtained.
The charging equipment of electric automobile Automotive maintenance and diagnosis management device that the present embodiment is provided, Plan rescheduling unit 13 is directed to each
The target charging equipment, adjusts accordingly according to its current state to its repair schedule；Maintenance program unit 14 is for working as
Front state is each described target charging equipment of failure, according to its current operational information, is obtained and it using Knowledge of Maintenance storehouse
Corresponding maintenance program.To the charging equipment in abnormal condition, patrolled and examined in time or keeped in repair, and then reduced equipment and occurred
The probability of failure, improves the utilization rate of equipment.
Preferably, the device can also include state model unit, for using decision Tree algorithms to sample data
It is analyzed, obtains the state evaluation model of the charging equipment.
The embodiment of the present invention provides a kind of charging equipment of electric automobile Automotive maintenance and diagnosis management device, shown in Figure 4, the dress
Put including：
Information acquisition unit 11, for obtaining the current operational information of all target charging equipments；
State evaluation unit 12, for for each described target charging equipment, according to its current operational information, using filling
The state evaluation model of electric equipment, obtains its current state, and the state includes normal, early warning, warning and failure；
Plan rescheduling unit 13, for for each described target charging equipment, meter being overhauled to it according to its current state
Draw and adjust accordingly；
Maintenance program unit 14, for being each described target charging equipment of failure for current state, works as according to it
Front operation information, using Knowledge of Maintenance storehouse corresponding maintenance program is obtained.
Failure predication unit 15, sets for charging for each described target that current state is normal, early warning or warning
It is standby, according to its current operational information, using the deterioration analysis model of charging equipment, predict its moment broken down；
Stock-keeping unit 16, for according to the corresponding fault message of each described target charging equipment, generating part warehouse
Deposit Managed Solution.
The device, can also include：Forecast model unit, for being carried out to sample data point using decision Tree algorithms
Analysis, obtains the deterioration analysis model of the charging equipment.
For device embodiment, because it essentially corresponds to embodiment of the method, so related part is referring to method reality
Apply the part explanation of example.Device embodiment described above is only schematic, wherein described as separating component
The unit of explanation can be or may not be physically separate, can be as the part that unit shows or can also
It is not physical location, you can be located at a place, or can also be distributed on multiple NEs.Can be according to reality
Need the purpose for selecting some or all of module therein to realize this embodiment scheme.Those of ordinary skill in the art are not
In the case of paying creative work, you can to understand and implement.
Herein, such as first and second or the like relational terms be used merely to by an entity or operation with it is another
One entity or operation make a distinction, and not necessarily require or imply these entities or there is any this reality between operating
Relation or order.And, term " including ", "comprising" or its any other variant are intended to the bag of nonexcludability
Contain, so that a series of process, method, article or equipment including key elements is not only including those key elements, but also including
Other key elements being not expressly set out, or also include the key element intrinsic for this process, method, article or equipment.
In the absence of more restrictions, the key element for being limited by sentence "including a ...", it is not excluded that including the key element
Process, method, article or equipment in also there is other identical element.
Each embodiment is described by the way of progressive in this specification, and what each embodiment was stressed is and other
The difference of embodiment, between each embodiment identical similar portion mutually referring to.
Described above to disclosed embodiment of this invention, enables professional and technical personnel in the field to realize or using this
Invention.Various modifications to these embodiments will be apparent for those skilled in the art, institute herein
The General Principle of definition can be realized in other embodiments without departing from the spirit or scope of the present invention.Therefore,
The present invention is not intended to be limited to the embodiments shown herein, and is to fit to special with principles disclosed herein and novelty
The consistent most wide scope of point.
Claims (8)
1. a kind of charging equipment of electric automobile Automotive maintenance and diagnosis management method, it is characterised in that include：
Obtain the current operational information of all target charging equipments；
For target charging equipment each described, according to its current operational information, using the state evaluation model of charging equipment, obtain
To its current state, the state includes normal, early warning, warning and failure；
For target charging equipment each described, its repair schedule is adjusted accordingly according to its current state；
For each described target charging equipment that current state is failure, according to its current operational information, using Knowledge of Maintenance
Storehouse obtains corresponding maintenance program.
2. method according to claim 1, it is characterised in that described for target charging equipment each described, according to
Its current operational information, using the state evaluation model of charging equipment, after obtaining its current state, also includes：
For each described target charging equipment that current state is normal, early warning or warning, according to its current operational information, profit
With the deterioration analysis model of charging equipment, its moment broken down is predicted；
According to the corresponding fault message of each described target charging equipment, Parts Inventory Managed Solution is generated.
3. method according to claim 2, it is characterised in that in the current operation for obtaining all target charging equipments
Before information, also include：
Sample data is analyzed using decision Tree algorithms, obtains the deterioration analysis model of the charging equipment.
4. method according to claim 1, it is characterised in that in the current operation for obtaining all target charging equipments
Before information, also include：
Sample data is analyzed using decision Tree algorithms, obtains the state evaluation model of the charging equipment.
5. a kind of charging equipment of electric automobile Automotive maintenance and diagnosis management device, it is characterised in that include：
Information acquisition unit, for obtaining the current operational information of all target charging equipments；
State evaluation unit, for for each described target charging equipment, according to its current operational information, using charging equipment
State evaluation model, obtain its current state, the state includes normal, early warning, warning and failure；
Plan rescheduling unit, for for each described target charging equipment, being carried out to its repair schedule according to its current state
Corresponding adjustment；
Maintenance program unit, for for each described target charging equipment that current state is failure, according to its current operation
Information, using Knowledge of Maintenance storehouse corresponding maintenance program is obtained.
6. device according to claim 5, it is characterised in that described device, also includes：
Failure predication unit, for for each described target charging equipment that current state is normal, early warning or warning, according to
Its current operational information, using the deterioration analysis model of charging equipment, predicts its moment broken down；
Stock-keeping unit, for according to the corresponding fault message of each described target charging equipment, generating Parts Inventory management
Scheme.
7. device according to claim 6, it is characterised in that described device, also includes：
Forecast model unit, for being analyzed to sample data using decision Tree algorithms, obtains the charging equipment
Deterioration analysis model.
8. device according to claim 5, it is characterised in that described device, also includes：
State model unit, for being analyzed to sample data using decision Tree algorithms, obtains the charging equipment
State evaluation model.
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| CN107168299A (en) * | 2017-07-05 | 2017-09-15 | 云南电网有限责任公司电力科学研究院 | A kind of method and system of charging pile fault diagnosis processing |
| CN107394295A (en) * | 2017-07-26 | 2017-11-24 | 万帮充电设备有限公司 | Charge the method and system prejudged |
| CN107633309A (en) * | 2017-09-22 | 2018-01-26 | 合肥工业大学 | A kind of maintenance policy of complicated former determines method and system |
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| CN108377017A (en) * | 2018-03-23 | 2018-08-07 | 万帮充电设备有限公司 | A kind of the charging method for early warning and device of charging pile |
| CN109615273A (en) * | 2019-01-16 | 2019-04-12 | 国网浙江省电力有限公司电力科学研究院 | A kind of electric car electrically-charging equipment method for evaluating state and system |
| CN109886328A (en) * | 2019-02-14 | 2019-06-14 | 国网浙江省电力有限公司电力科学研究院 | A kind of electric car electrically-charging equipment failure prediction method and system |
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| CN114435172B (en) * | 2022-03-01 | 2022-11-22 | 深圳市中鑫新能源科技有限公司 | Automatically-managed intelligent charging pile and intelligent charging method for new energy automobile |
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Address after: 250000 Electric Power Intelligent Robot Production Project 101 in Jinan City, Shandong Province, South of Feiyue Avenue and East of No. 26 Road (ICT Industrial Park) Applicant after: National Network Intelligent Technology Co., Ltd. Address before: Xinluo Avenue high tech Zone of Ji'nan City, Shandong province 250101 silver bearing No. 2008 building Applicant before: Shandong Luneng Intelligent Technology Co., Ltd. |
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Application publication date: 20170510 |