CN115782584A - New energy vehicle safety state determination method, system, equipment and medium - Google Patents
New energy vehicle safety state determination method, system, equipment and medium Download PDFInfo
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Abstract
The method comprises the steps of obtaining real-time battery characteristic data and historical battery characteristic data, performing completion processing on missing data in the historical battery characteristic data to obtain completion data, obtaining a plurality of common core characteristics according to each historical battery characteristic data in the completion data and the number of historical overheated vehicles, determining boundary values of the common core characteristics according to the completion data corresponding to each common core characteristic, and determining the safety state of the new energy vehicle based on the real-time battery characteristic data corresponding to each common core characteristic and the corresponding boundary values.
Description
Technical Field
The invention relates to the technical field of automobiles, in particular to a method, a system, equipment and a medium for determining the safety state of a new energy vehicle.
Background
In recent years, with the increasing of the holding capacity of new energy automobiles, spontaneous combustion accidents caused by battery thermal runaway are more and more, and serious loss is brought to vehicle enterprises and users. The battery thermal runaway refers to a phenomenon that the battery temperature rapidly rises due to a series of chemical reactions caused by the battery temperature to a certain degree, and the battery thermal runaway can be caused due to the reasons of overhigh temperature, overcharge and overdischarge, external short circuit, water inflow, collision and the like in a local area, so that spontaneous combustion accidents are caused.
Early warning monitoring is carried out through big data among the correlation technique, discerns the high risk vehicle in advance, and then effectively avoids the battery thermal runaway that the battery overheated causes. For example, patent document CN111126449A discloses a battery fault classification diagnosis method based on cluster analysis, which includes: the data of the voltage difference, the temperature difference, the average current, the average speed and the like recorded by the battery in a period of time are taken as 4 important indexes for clustering induction, and after normalization processing, the data mining of clustering analysis is carried out on various problems recorded by the battery by using a K-means method. The method can be used for mining the association between the battery data from a deeper level, better classifying various batteries, and further enabling managers to obtain more complete results with higher efficiency during information retrieval. However, the algorithm development is carried out from the data-driven dimension, the method has no interpretability, the prediction result is easily influenced by the number of vehicle samples, different results are caused by different numbers of vehicles in samples, and the high risk of the battery cannot be accurately judged.
Disclosure of Invention
One of the purposes of the invention is to provide a new energy vehicle safety state determination method, so as to solve the technical problems that battery fault diagnosis based on a cluster analysis method in the related technology has no interpretability, the prediction result is easily influenced by the number of vehicle samples, different results are caused by different numbers of vehicles in samples, and the high risk of the battery cannot be accurately judged; the second purpose is to provide a new energy vehicle safety state determining system; it is a third object to provide an electronic device; it is a fourth object to provide a storage medium.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
in a first aspect, the present application provides a new energy vehicle safety state determination method, including:
acquiring real-time battery characteristic data and historical battery characteristic data, wherein the real-time battery characteristic data are data of battery characteristic parameters of a new energy vehicle to be determined in a safe state, the historical battery characteristic data comprise data of the battery characteristic parameters of a plurality of historical overheated vehicles and a plurality of historical normal vehicles within the same time length, and the number of the historical overheated vehicles is acquired, the historical overheated vehicles, the historical normal vehicles and the new energy vehicle are of the same vehicle type, and the number of the historical normal vehicles is the same as the number of the historical overheated vehicles;
performing completion processing on missing data in the historical battery characteristic data to obtain completion data;
obtaining a plurality of common core characteristics according to the historical battery characteristic data in the completion data and the number of the historical overheated vehicles, wherein the common core characteristics are the common core characteristics between the historical battery characteristic data of the historical overheated vehicles and the historical battery characteristic data of the historical normal vehicles;
determining a boundary value of each common core characteristic according to the completion data corresponding to the common core characteristics;
and determining the safety state of the new energy vehicle based on the real-time battery characteristic data corresponding to each common core characteristic and the corresponding boundary value.
In an exemplary embodiment of the present application, several common core features are obtained, including:
determining the core characteristics of the overheated vehicles according to the completion data of the historical overheated vehicles, the number of the historical overheated vehicles and a first preset battery characteristic parameter threshold;
determining core characteristics of the normal vehicles based on the completion data of the historical normal vehicles, the number of the historical overheated vehicles and a second preset battery characteristic parameter threshold;
based on the overheated vehicle core characteristic and the normal vehicle core characteristic, a plurality of common core characteristics are obtained.
In an exemplary embodiment of the present application, determining the overheated vehicle core characteristic includes:
determining a first average value of corresponding battery characteristic parameters according to the completion data of each historical overheated vehicle;
determining a first average absolute error or a first mean square error of each corresponding battery characteristic parameter according to the completion data, the first average value and the number of the historical overheated vehicles;
and determining the core characteristics of the overheated vehicle according to the first mean absolute error or the first mean square error and a first preset battery characteristic parameter threshold.
In an exemplary embodiment of the present application, determining normal vehicle core characteristics includes:
determining a second average value of the corresponding battery characteristic parameters according to the completion data of each historical normal vehicle;
determining a second average absolute error or a second mean square error of each corresponding battery characteristic parameter according to the completion data of each historical normal vehicle, the second average value and the number of the historical overheated vehicles;
and determining the core characteristics of the normal vehicle according to the second mean absolute error or the second mean square error and a second preset battery characteristic parameter threshold.
In an exemplary embodiment of the present application, determining the boundary value of the common core feature comprises:
comparing the completion data of the historical overheated vehicles corresponding to the common core characteristics to obtain a first minimum value or a first maximum value;
comparing the completion data of the historical normal vehicles corresponding to the common core features to obtain a second minimum value or a second maximum value;
the boundary value of the common core feature is determined from the first minimum value and the second minimum value or from the first maximum value and the second maximum value.
In an exemplary embodiment of the present application, determining the safety state of the new energy vehicle includes:
determining deviation based on real-time battery characteristic data corresponding to each common core characteristic and a corresponding boundary value;
and determining the safety state of the new energy vehicle based on the deviation and the preset weight of each common core characteristic.
In an exemplary embodiment of the present application, determining the safety state of the new energy vehicle includes:
determining the safety index of the new energy vehicle according to the deviation and the weight of each preset common core characteristic;
and determining the safety state of the new energy vehicle based on the safety index and a preset safety index threshold.
In a second aspect, the present application provides a new energy vehicle safety status determination system, including:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring real-time battery characteristic data and historical battery characteristic data, the real-time battery characteristic data is data of battery characteristic parameters of a new energy vehicle to be determined in a safe state, the historical battery characteristic data comprises data of the battery characteristic parameters of a plurality of historical overheated vehicles and a plurality of historical normal vehicles within the same time length, and the number of the historical overheated vehicles is acquired, the historical overheated vehicles, the historical normal vehicles and the new energy vehicle are of the same vehicle type, and the number of the historical normal vehicles is the same as the number of the historical overheated vehicles;
the preprocessing module is used for performing completion processing on missing data in the historical battery characteristic data to obtain completion data;
the first determining module is used for obtaining a plurality of common core characteristics according to each historical battery characteristic data in the completion data and the number of the historical overheated vehicles, wherein the common core characteristics are common core characteristics between the historical battery characteristic data of the historical overheated vehicles and the historical battery characteristic data of the historical normal vehicles;
the second determining module is used for determining the boundary value of each common core characteristic according to the completion data corresponding to the common core characteristic;
and the third determining module is used for determining the safety state of the new energy vehicle based on the real-time battery characteristic data corresponding to each common core characteristic and the corresponding boundary value.
In a third aspect, the present application provides an electronic device comprising:
one or more processors;
a storage device for storing one or more programs that, when executed by the one or more processors, cause the electronic device to implement the new energy vehicle safety state determination method as described above.
In a fourth aspect, the present application provides a computer-readable storage medium, characterized in that a computer program is stored thereon, which, when executed by a processor of a computer, causes the computer to execute the new energy vehicle safety state determination method as described above.
The invention has the beneficial effects that:
the method comprises the steps of obtaining real-time battery characteristic data and historical battery characteristic data, wherein the real-time battery characteristic data are data of battery characteristic parameters of a new energy vehicle of which the safety state is to be determined, the historical battery characteristic data comprise data of the battery characteristic parameters of a plurality of historical overheated vehicles and a plurality of historical normal vehicles within the same time, obtaining the number of the historical overheated vehicles, the historical normal vehicles and the new energy vehicle are of the same type, the number of the historical normal vehicles is the same as that of the historical overheated vehicles, performing completion processing on missing data in the historical battery characteristic data to obtain completion data, determining the safety state of the new energy vehicle according to each historical battery characteristic data in the completion data and the number of the historical overheated vehicles to obtain a plurality of common core characteristics, determining the safety state of the new energy vehicle according to the completion data corresponding to each common core characteristic, determining the boundary value of each common core characteristic based on the real-time battery characteristic data corresponding to each common core characteristic and the corresponding boundary value, determining the safety state of the new energy vehicle by a clear logical relationship, and further solving the problem that the high-risk caused by the fact that the high-risk of the vehicle is caused by different sample numbers of the real-time battery characteristic data corresponding to the real-time battery characteristic data and the prediction results.
Drawings
Fig. 1 is a flowchart illustrating a new energy vehicle safety state determination method according to an exemplary embodiment of the present application;
FIG. 2 is a flowchart of an exemplary embodiment of obtaining a number of common core features in step S130 in the embodiment shown in FIG. 1;
FIG. 3 is a flowchart of the determination of the core characteristics of the overheated vehicle at step S210 in the embodiment of FIG. 2 in an exemplary embodiment;
FIG. 4 is a flow chart of the determination of normal vehicle core characteristics in step S220 of the embodiment of FIG. 2 in an exemplary embodiment;
FIG. 5 is a flowchart of the determination of the boundary value of the common core feature in step S140 in the embodiment shown in FIG. 1 in an exemplary embodiment;
fig. 6 is a flowchart of the determination of the safety state of the new-energy vehicle in step S150 in the embodiment shown in fig. 1 in an exemplary embodiment;
fig. 7 is a flowchart of the determination of the safety state of the new-energy vehicle in step S620 in the embodiment shown in fig. 6 in an exemplary embodiment;
FIG. 8 is a flow diagram of a method for determining a safe state of a new energy vehicle, according to an exemplary embodiment;
fig. 9 is a block diagram of a new energy vehicle safety state determination system shown in an exemplary embodiment of the present application;
FIG. 10 illustrates a schematic structural diagram of a computer system suitable for use to implement the electronic device of the embodiments of the subject application.
Detailed Description
Other advantages and effects of the present invention will become apparent to those skilled in the art from the disclosure herein, wherein the embodiments of the present invention are described in detail with reference to the accompanying drawings and preferred embodiments. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It should be understood that the preferred embodiments are illustrative of the invention only and are not limiting upon the scope of the invention.
In the following description, numerous details are set forth to provide a more thorough explanation of embodiments of the present invention, however, it will be apparent to one skilled in the art that embodiments of the present invention may be practiced without these specific details, and in other embodiments, well-known structures and devices are shown in block diagram form, rather than in detail, in order to avoid obscuring embodiments of the present invention.
Referring to fig. 1, fig. 1 is a flowchart of a new energy vehicle safety state determination method according to an exemplary embodiment of the present application, where the new energy vehicle safety state determination method is used to determine a safety state of a new energy vehicle, so as to solve technical problems that a battery fault is diagnosed based on a cluster analysis method in the related art, the battery fault has no interpretability, a prediction result is easily affected by vehicle sample numbers, and different sample vehicle numbers cause different results, which results in a high risk that the battery cannot be accurately determined.
As shown in fig. 1, in an exemplary embodiment of the present application, the new energy vehicle safety state determination method at least includes steps S110 to S150, which are described in detail as follows:
step S110, acquiring real-time battery characteristic data and historical battery characteristic data, wherein the real-time battery characteristic data are data of battery characteristic parameters of new energy vehicles in a safety state to be determined, the historical battery characteristic data comprise data of the battery characteristic parameters of a plurality of historical overheated vehicles and a plurality of historical normal vehicles within the same time length, and the number of the historical overheated vehicles is acquired, the historical overheated vehicles, the historical normal vehicles and the new energy vehicles are of the same vehicle type, and the number of the historical normal vehicles is the same as that of the historical overheated vehicles;
the battery may be a lithium battery, and the characteristic parameters of the battery include total mileage, average daily mileage, battery life, static maximum differential pressure, dynamic maximum differential pressure, maximum charge differential temperature, minimum insulation resistance value, fast charge ratio, historical fault, minimum insulation times, charge-end SOC ratio, energy recovery current ratio, SOC ratio during energy recovery, and the like;
s120, performing completion processing on missing data in the historical battery characteristic data to obtain completion data;
s130, obtaining a plurality of common core characteristics according to the characteristic data of each historical battery in the completion data and the quantity of the historical overheated vehicles;
the common core feature is a common core feature between historical battery feature data of historical overheated vehicles and historical battery feature data of historical normal vehicles;
s140, determining a boundary value of each common core characteristic according to the completion data corresponding to each common core characteristic;
and S150, determining the safety state of the new energy vehicle based on the real-time battery characteristic data corresponding to each common core characteristic and the corresponding boundary value.
In the related art, the battery fault is diagnosed based on cluster analysis. The inventor analyzes the related technology and finds that the method is adopted to diagnose the battery fault, the related technology diagnoses the battery fault based on a cluster analysis method, the interpretability is not available, the prediction result is easily influenced by the number of vehicle samples, the results are different due to the number of vehicles in different samples, and the high risk problem that the battery cannot be accurately judged is caused. The method includes the steps of obtaining real-time battery characteristic data and historical battery characteristic data, wherein the real-time battery characteristic data are data of battery characteristic parameters of new energy vehicles of which safety states are to be determined, the historical battery characteristic data comprise data of the battery characteristic parameters of a plurality of historical overheated vehicles and a plurality of historical normal vehicles in the same time duration, obtaining the number of historical overheated vehicles, the historical normal vehicles and the new energy vehicles are of the same vehicle type, the number of the historical normal vehicles is the same as the number of the historical overheated vehicles, conducting completion processing on missing data in the historical battery characteristic data to obtain completion data, obtaining a plurality of common core characteristics according to each historical battery characteristic data in the completion data and the number of the historical overheated vehicles, determining boundary values of the common core characteristics according to the completion data corresponding to each common core characteristic, determining the safety states of the new energy vehicles based on the real-time battery characteristic data corresponding to each common core characteristic and the corresponding boundary values, determining the safety states of the new energy vehicles through clear logical relations, and further solving the problems that battery failure diagnosis based on cluster analysis, interpretability, prediction results of the vehicles are susceptible to different sample numbers, and the vehicles cannot be accurately judged by the high risk.
Referring to fig. 2, fig. 2 is a flowchart illustrating an exemplary embodiment of obtaining a plurality of common core features in step S130 in the embodiment shown in fig. 1.
As shown in fig. 2, in an exemplary embodiment of the present application, the process of obtaining several common core features in step S130 in the embodiment shown in fig. 1 includes steps S210 to S230, which are described in detail as follows:
s210, determining the core characteristics of the overheated vehicles according to the completion data of the historical overheated vehicles, the number of the historical overheated vehicles and a first preset battery characteristic parameter threshold;
s220, determining core characteristics of the normal vehicles based on the completion data of the historical normal vehicles, the number of the historical overheated vehicles and a second preset battery characteristic parameter threshold;
and S230, obtaining a plurality of common core characteristics based on the core characteristics of the overheated vehicle and the core characteristics of the normal vehicle.
Specifically, the core features included in both the overheated vehicle core feature and the normal vehicle core feature are the common core features.
Referring to FIG. 3, FIG. 3 is a flowchart of the determination of the overheated vehicle core characteristic of step S210 of the embodiment of FIG. 2 in an exemplary embodiment.
As shown in fig. 3, in an exemplary embodiment of the present application, the process of determining the overheated vehicle core characteristic in step S210 in the embodiment shown in fig. 2 includes steps S310 to S330, which are described in detail as follows:
s310, determining a first average value of corresponding battery characteristic parameters according to the completion data of each historical overheated vehicle;
s320, determining a first average absolute error or a first mean square error of each corresponding battery characteristic parameter according to the completion data, the first average value and the number of the historical overheated vehicles;
specifically, a first mean absolute error and a first mean square error are respectively determined according to a formula (I) and a formula (II);
wherein MAE is the first mean absolute error, MSE is the first mean square error, o i The complement data of the battery characteristic parameter of the ith historically overheated vehicle,
is a first average of the completion data of the corresponding battery characteristic parameter, and n is the number of the historically overheated vehicles.
And S330, determining the core characteristics of the overheated vehicle according to the first average absolute error or the first mean square error and a first preset battery characteristic parameter threshold.
Specifically, the first average absolute error or the first mean square error is compared with a first preset battery characteristic parameter threshold, and if the first average absolute error or the first mean square error is smaller than the first preset battery characteristic parameter threshold, the parameter corresponding to the first average absolute error or the first mean square error is determined as the core characteristic of the overheated vehicle. Different first preset battery characteristic parameter thresholds may be set for the first mean absolute error and the first mean square error. The first predetermined battery characteristic parameter threshold may be set by itself, and will not be described herein.
Referring to FIG. 4, FIG. 4 is a flowchart of the determination of the overheated vehicle core characteristic at step S210 of the embodiment of FIG. 2 in an exemplary embodiment.
As shown in fig. 4, in an exemplary embodiment of the present application, the process of determining the normal vehicle core characteristic in step S220 in the embodiment shown in fig. 2 includes steps S410 to S430, which are described in detail as follows:
s410, determining a second average value of the corresponding battery characteristic parameters according to the completion data of each historical normal vehicle;
s420, determining a second average absolute error or a second mean square error of each corresponding battery characteristic parameter according to the completion data, the second average value and the number of the historical overheated vehicles of each historical normal vehicle;
specifically, a second mean absolute error and a second mean square error are respectively determined according to a formula (III) and a formula (IV);
wherein MAE 'is the second mean absolute error, MSE' is the second mean square error, o i' The complement data of the battery characteristic parameter of the ith historically normal vehicle,
and n' is a second average value of the complementary data of the corresponding battery characteristic parameter, and the number of the historical overheated vehicles.
And S430, determining the core characteristics of the normal vehicle according to the second mean absolute error or the second mean square error and a second preset battery characteristic parameter threshold.
Specifically, the second average absolute error or the second mean square error is compared with a second preset battery characteristic parameter threshold, and if the second average absolute error or the second mean square error is smaller than the second preset battery characteristic parameter threshold, the parameter corresponding to the second average absolute error or the second mean square error is determined as the core characteristic of the normal vehicle.
Referring to fig. 5, fig. 5 is a flowchart of the exemplary embodiment of determining the boundary value of the common core feature in step S140 shown in fig. 1.
As shown in fig. 5, in an exemplary embodiment of the present application, the process of determining the boundary value of the common core feature in step S140 in the embodiment shown in fig. 1 includes steps S510 to S540, which are described in detail as follows:
s510, comparing the completion data of the historical overheated vehicles corresponding to the common core characteristics to obtain a first minimum value or a first maximum value;
s520, comparing the completion data of the historical normal vehicles corresponding to the common core characteristics to obtain a second minimum value or a second maximum value;
step S530, determining a boundary value of the common core characteristic according to the first minimum value and the second minimum value or according to the first maximum value and the second maximum value;
specifically, the average value of the first minimum value and the second minimum value or the average value of the first maximum value and the second maximum value is the boundary value of the corresponding core feature.
Referring to fig. 6, fig. 6 is a flowchart illustrating the determination of the safety state of the new-energy vehicle in step S150 in the embodiment shown in fig. 1 in an exemplary embodiment.
As shown in fig. 6, in an exemplary embodiment of the application, the process of determining the safety state of the new-energy vehicle in step S150 in the embodiment shown in fig. 1 includes steps S610 to S620, and the following is described in detail:
s610, determining deviation based on real-time battery characteristic data corresponding to the common core characteristics and corresponding boundary values;
specifically, the difference between the real-time battery characteristic data corresponding to each common core characteristic and the corresponding boundary value is the deviation.
And S620, determining the safety state of the new energy vehicle based on the deviation and the weight of each preset common core characteristic.
Referring to fig. 7, fig. 7 is a flowchart illustrating the determination of the safety state of the new-energy vehicle in step S620 in the embodiment shown in fig. 6 in an exemplary embodiment.
As shown in fig. 7, in an exemplary embodiment of the present application, the process of determining the safety state of the new energy vehicle in step S620 in the embodiment shown in fig. 6 includes steps S710 to S720, which are described in detail as follows:
s710, determining a safety index of the new energy vehicle according to the deviation and the weight of each preset common core characteristic;
specifically, the sum of products of the deviation and the weight of each corresponding preset common core feature is the safety index of the new energy vehicle.
And S720, determining the safety state of the new energy vehicle based on the safety index and a preset safety index threshold value.
Specifically, the safety index is compared with a preset safety index threshold, and if the safety index is larger than the preset safety index threshold, the safety state of the new energy vehicle is determined to be at risk.
As shown in fig. 8, in a specific embodiment, the new energy vehicle safety state determining method includes the following steps:
acquiring real-time battery characteristic data and historical battery characteristic data, wherein the real-time battery characteristic data are data of battery characteristic parameters of a new energy vehicle (namely a vehicle needing monitoring) in a safety state to be determined, the historical battery characteristic data comprise data of the battery characteristic parameters of a plurality of historical overheated vehicles and a plurality of historical normal vehicles within the same time length, and the number of the historical overheated vehicles is acquired, the historical overheated vehicles, the historical normal vehicles and the new energy vehicle are of the same type, and the number of the historical normal vehicles is the same as the number of the historical overheated vehicles; the battery is a lithium battery, and the characteristic parameters of the battery comprise total mileage, daily average mileage, battery life, static maximum differential pressure, dynamic maximum differential pressure, maximum charging differential temperature, lowest insulation resistance value, fast charging ratio, historical fault, lowest insulation times, SOC ratio after charging, energy recovery current ratio, SOC ratio during energy recovery and the like;
performing completion processing on missing data in the historical battery characteristic data to obtain completion data;
determining a first average value of corresponding battery characteristic parameters according to the completion data of each historical overheated vehicle;
respectively determining a first mean absolute error and a first mean square error according to a formula (I) and a formula (II);
wherein MAE is the first mean absolute error, MSE is the first mean square error, o i For the complement data of the battery characteristic parameter of the ith historically overheated vehicle,
a first average of the completion data for the corresponding battery characteristic parameter, n being the number of historically overheated vehicles;
and specifically, comparing the first average absolute error or the first mean square error with a first preset battery characteristic parameter threshold, and if the first average absolute error or the first mean square error is smaller than the first preset battery characteristic parameter threshold, determining the battery characteristic parameter corresponding to the first average absolute error or the first mean square error as the overheated vehicle core characteristic. For the first mean absolute error and the first mean square error, different first preset battery characteristic parameter thresholds can be set;
determining a second average value of the corresponding battery characteristic parameters according to the completion data of each historical normal vehicle;
determining a second mean absolute error and a second mean square error according to the formula (III) and the formula (IV) respectively;
wherein MAE 'is the second mean absolute error, MSE' is the second mean square error, o i' The complement data of the battery characteristic parameter of the ith historically normal vehicle,
a second average of the completion data for the corresponding battery characteristic parameter, n' being the number of historically overheated vehicles;
determining a core characteristic of the normal vehicle according to the second average absolute error or the second mean-square error and a second preset battery characteristic parameter threshold, specifically, comparing the second average absolute error or the second mean-square error with the second preset battery characteristic parameter threshold, and if the second average absolute error or the second mean-square error is smaller than the second preset battery characteristic parameter threshold, determining a battery characteristic parameter corresponding to the second average absolute error or the second mean-square error as the core characteristic of the normal vehicle;
comparing the overheated vehicle core characteristic with the normal vehicle core characteristic, wherein the core characteristics contained in the overheated vehicle core characteristic and the normal vehicle core characteristic are common core characteristics;
the completion data of the historical overheated vehicles corresponding to the common core characteristics are compared to obtain a first minimum value or a first maximum value;
the completion data of the historical normal vehicles corresponding to the common core features are compared to obtain a second minimum value or a second maximum value;
calculating the average value of the first minimum value and the second minimum value or calculating the average value of the first maximum value and the second maximum value to obtain the boundary value of the corresponding core characteristic;
calculating the difference value between the real-time battery characteristic data corresponding to each common core characteristic and the corresponding boundary value to obtain deviation (namely deviation degree);
determining the safety index of the new energy vehicle according to the deviation and the preset weight of each common core characteristic, specifically, multiplying the deviation by the corresponding preset weight of each common core characteristic, and then summing to obtain the safety index (namely the final score) of the new energy vehicle;
and comparing the safety index with a preset safety index threshold value, determining the safety state of the new energy vehicle, and if the safety index is equal to the preset safety index threshold value, determining that the safety state has risks (namely high risks).
Referring to fig. 9, an embodiment of the present application further provides a new energy vehicle safety state determination system M900, where the new energy vehicle safety state determination system M900 includes:
the first acquisition module M910 is configured to acquire real-time battery characteristic data and historical battery characteristic data, where the real-time battery characteristic data is data of battery characteristic parameters of a new energy vehicle in a safety state to be determined, the historical battery characteristic data includes data of battery characteristic parameters of a plurality of historical overheated vehicles and a plurality of historical normal vehicles within the same time, and the number of the historical overheated vehicles is acquired, the historical overheated vehicles, the historical normal vehicles and the new energy vehicle are of the same vehicle type, and the number of the historical normal vehicles is the same as the number of the historical overheated vehicles;
the preprocessing module M920 is used for performing completion processing on missing data in the historical battery characteristic data to obtain completion data;
the first determining module M930 is configured to obtain a plurality of common core features according to each historical battery feature data in the completion data and the number of the historical overheated vehicles, where the common core features are common core features between the historical battery feature data of the historical overheated vehicles and the historical battery feature data of the historical normal vehicles;
a second determining module M940, configured to determine a boundary value of each common core feature according to the completion data corresponding to the common core feature;
and the third determining module M950 is configured to determine the safety state of the new energy vehicle based on the real-time battery characteristic data corresponding to each common core characteristic and the corresponding boundary value.
It should be noted that the new energy vehicle safety state determination system provided in the above embodiment and the new energy vehicle safety state determination method provided in the above embodiment belong to the same concept. The specific manner in which each module and unit performs operations has been described in detail in the method embodiment, and is not described here any more. In practical applications, the new energy vehicle safety status determining system provided in the above embodiment may distribute the above functions to different functional modules according to needs, that is, divide the internal structure of the device into different functional modules to complete all or part of the above described functions, which is not limited herein.
Embodiments of the present application further provide an electronic device, including: one or more processors; a storage device configured to store one or more programs, which when executed by the one or more processors, cause the electronic apparatus to implement the new energy vehicle safety state determination method provided in each of the above embodiments.
FIG. 10 illustrates a schematic structural diagram of a computer system suitable for use in implementing the electronic device of an embodiment of the present application. It should be noted that the computer system 1000 of the electronic device shown in fig. 10 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 10, the computer system 1000 includes a Central Processing Unit (CPU) 1001 that can perform various appropriate actions and processes, such as performing the methods described in the above embodiments, according to a program stored in a Read-Only Memory (ROM) 1002 or a program loaded from a storage portion 1008 into a Random Access Memory (RAM) 1003. In the RAM 1003, various programs and data necessary for system operation are also stored. The CPU1001, ROM 1002, and RAM 1003 are connected to each other by a bus 1004. An Input/Output (I/O) interface 1005 is also connected to the bus 1004.
The following components are connected to the I/O interface 1005: an input section 1006 including a keyboard, a mouse, and the like; an output section 1007 including a Display panel such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and a speaker; a storage portion 1008 including a hard disk and the like; and a communication section 1009 including a Network interface card such as a Local Area Network (LAN) card, a modem, or the like. The communication section 1009 performs communication processing via a network such as the internet. The driver 1010 is also connected to the I/O interface 1005 as necessary. A removable medium 1011 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 1010 as necessary, so that a computer program read out therefrom is mounted into the storage section 1008 as necessary.
In particular, according to embodiments of the application, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising a computer program for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication part 1009 and/or installed from the removable medium 1011. When the computer program is executed by a Central Processing Unit (CPU) 1001, various functions defined in the system of the present application are executed.
It should be noted that the computer readable medium shown in the embodiments of the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium may be, for example, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read-Only Memory (ROM), an Erasable Programmable Read-Only Memory (EPROM), a flash Memory, an optical fiber, a portable Compact Disc Read-Only Memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer-readable signal medium may include a propagated data signal with a computer program embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. The computer program embodied on the computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. Each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software, or may be implemented by hardware, and the described units may also be disposed in a processor. The names of these elements do not in some cases constitute limitations on the elements themselves.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor of a computer, causes the computer to execute the new energy vehicle safety state determination method as described above. The computer-readable storage medium may be included in the electronic device described in the above embodiment, or may be separately present without being incorporated in the electronic device.
Another aspect of the application also provides a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions, so that the computer device executes the new energy vehicle safety state determination method provided in the above embodiments.
The above embodiments are merely preferred embodiments for fully illustrating the present invention, and the scope of the present invention is not limited thereto. The equivalent substitution or change made by the technical personnel in the technical field on the basis of the invention is all within the protection scope of the invention.
Claims (10)
1. A new energy vehicle safety state determination method is characterized by comprising the following steps:
acquiring real-time battery characteristic data and historical battery characteristic data, wherein the real-time battery characteristic data are data of battery characteristic parameters of new energy vehicles of which the safety states are to be determined, the historical battery characteristic data comprise data of the battery characteristic parameters of a plurality of historical overheated vehicles and a plurality of historical normal vehicles within the same time length respectively, and acquiring the number of the historical overheated vehicles, the historical overheated vehicles and the new energy vehicles are of the same vehicle type, and the number of the historical normal vehicles is the same as that of the historical overheated vehicles;
performing completion processing on missing data in the historical battery characteristic data to obtain completion data;
obtaining a plurality of common core characteristics according to the historical battery characteristic data in the completion data and the number of the historical overheated vehicles, wherein the common core characteristics are the common core characteristics between the historical battery characteristic data of the historical overheated vehicles and the historical battery characteristic data of the historical normal vehicles;
determining a boundary value of each common core characteristic according to the completion data corresponding to the common core characteristics;
and determining the safety state of the new energy vehicle based on the real-time battery characteristic data corresponding to each common core characteristic and the corresponding boundary value.
2. The new energy vehicle safety state determination method according to claim 1, wherein obtaining a plurality of common core features comprises:
determining the core characteristics of the overheated vehicles according to the completion data of the historical overheated vehicles, the number of the historical overheated vehicles and a first preset battery characteristic parameter threshold;
determining core characteristics of the normal vehicles based on the completion data of the historical normal vehicles, the number of the historical overheated vehicles and a second preset battery characteristic parameter threshold;
based on the overheated vehicle core characteristic and the normal vehicle core characteristic, a plurality of common core characteristics are obtained.
3. The new energy vehicle safety state determination method according to claim 2, wherein determining an overheated vehicle core characteristic includes:
determining a first average value of corresponding battery characteristic parameters according to the completion data of each historical overheated vehicle;
determining a first average absolute error or a first mean square error of each corresponding battery characteristic parameter according to the completion data, the first average value and the number of the historical overheated vehicles;
and determining the core characteristic of the overheated vehicle according to the first average absolute error or the first mean square error and a first preset battery characteristic parameter threshold.
4. The new energy vehicle safety state determination method according to claim 2, wherein determining a normal vehicle core characteristic includes:
determining a second average value of the corresponding battery characteristic parameters according to the completion data of each historical normal vehicle;
determining a second average absolute error or a second mean square error of each corresponding battery characteristic parameter according to the completion data of each historical normal vehicle, the second average value and the number of historical overheated vehicles;
and determining the core characteristics of the normal vehicle according to the second average absolute error or the second mean square error and a second preset battery characteristic parameter threshold.
5. The new energy vehicle safety state determination method according to claim 1, wherein determining the boundary value of the common core characteristic includes:
comparing the completion data of the historical overheated vehicles corresponding to the common core characteristics to obtain a first minimum value or a first maximum value;
comparing the completion data of the historical normal vehicles corresponding to the common core features to obtain a second minimum value or a second maximum value;
the boundary value of the common core feature is determined from the first minimum value and the second minimum value or from the first maximum value and the second maximum value.
6. The new energy vehicle safety state determination method according to claim 1, wherein determining the safety state of the new energy vehicle includes:
determining deviation based on real-time battery characteristic data corresponding to each common core characteristic and a corresponding boundary value;
and determining the safety state of the new energy vehicle based on the deviation and the preset weight of each common core characteristic.
7. The new energy vehicle safety state determination method according to claim 6, wherein determining the safety state of the new energy vehicle includes:
determining the safety index of the new energy vehicle according to the deviation and the weight of each preset common core characteristic;
and determining the safety state of the new energy vehicle based on the safety index and a preset safety index threshold.
8. A new energy vehicle safety state determination system, characterized by comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring real-time battery characteristic data and historical battery characteristic data, the real-time battery characteristic data is data of battery characteristic parameters of a new energy vehicle of which the safety state is to be determined, the historical battery characteristic data comprises data of the battery characteristic parameters of a plurality of historical overheated vehicles and a plurality of historical normal vehicles within the same time length, and the quantity of the historical overheated vehicles is acquired, the historical overheated vehicles, the historical normal vehicles and the new energy vehicle are of the same vehicle type, and the quantity of the historical normal vehicles is the same as the quantity of the historical overheated vehicles;
the preprocessing module is used for performing completion processing on missing data in the historical battery characteristic data to obtain completion data;
the first determining module is used for obtaining a plurality of common core characteristics according to each historical battery characteristic data in the completion data and the number of the historical overheated vehicles, wherein the common core characteristics are common core characteristics between the historical battery characteristic data of the historical overheated vehicles and the historical battery characteristic data of the historical normal vehicles;
the second determining module is used for determining the boundary value of each common core characteristic according to the completion data corresponding to the common core characteristic;
and the third determining module is used for determining the safety state of the new energy vehicle based on the real-time battery characteristic data corresponding to each common core characteristic and the corresponding boundary value.
9. An electronic device, characterized in that the electronic device comprises:
one or more processors;
storage means for storing one or more programs that, when executed by the one or more processors, cause the electronic device to implement the new energy vehicle safety state determination method as recited in any one of claims 1-7.
10. A computer-readable storage medium, characterized in that a computer program is stored thereon, which, when executed by a processor of a computer, causes the computer to execute the new energy vehicle safety state determination method according to any one of claims 1 to 7.
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