CN116184219A - New energy automobile driving motor performance detecting system - Google Patents

New energy automobile driving motor performance detecting system Download PDF

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Publication number
CN116184219A
CN116184219A CN202310220195.XA CN202310220195A CN116184219A CN 116184219 A CN116184219 A CN 116184219A CN 202310220195 A CN202310220195 A CN 202310220195A CN 116184219 A CN116184219 A CN 116184219A
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China
Prior art keywords
lithium battery
ternary lithium
new energy
energy automobile
charge
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CN202310220195.XA
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Chinese (zh)
Inventor
陈阔
崔臻
蒋剑
陶广华
杜克虎
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Hangzhou Hemei Automobile Technology Co Ltd
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Hangzhou Hemei Automobile Technology Co Ltd
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Priority to CN202310220195.XA priority Critical patent/CN116184219A/en
Publication of CN116184219A publication Critical patent/CN116184219A/en
Withdrawn legal-status Critical Current

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/378—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC] specially adapted for the type of battery or accumulator
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/3644—Constructional arrangements
    • G01R31/3647—Constructional arrangements for determining the ability of a battery to perform a critical function, e.g. cranking
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/3644—Constructional arrangements
    • G01R31/3648—Constructional arrangements comprising digital calculation means, e.g. for performing an algorithm
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)
  • Tests Of Electric Status Of Batteries (AREA)

Abstract

The invention relates to a new energy automobile driving motor performance detection system, which comprises: the frequency prediction mechanism is used for predicting the charge cycle frequency from the current moment to the future moment when the maximum battery capacity of the ternary lithium battery drops to eighty percent of the maximum battery capacity of the ternary lithium battery in a factory state by adopting an artificial intelligent model based on the latest starting parameter, the working temperature and the charge-discharge time length of the ternary lithium battery of the new energy automobile, and outputting the charge cycle frequency as the predicted residual cycle frequency; and the replacement notification mechanism is used for sending a replacement notification signal when the accumulated charge cycle times of the ternary lithium battery reaches the predicted residual cycle times after the current moment. According to the invention, the number of remaining charging cycles from the current moment to the replacement of the battery can be intelligently predicted on the basis of customizing the artificial intelligent model, so that a reliable detection mode is provided for the performance of the driving motor of the new energy automobile.

Description

New energy automobile driving motor performance detecting system
Technical Field
The invention relates to the field of new energy automobiles, in particular to a new energy automobile driving motor performance detection system.
Background
The battery is a main driving motor of the new energy automobile, the ternary lithium battery is one of the main batteries of the new energy automobile, and the service life and the replacement time of the ternary lithium battery are determined by the following elements.
Firstly, the starting habit of a driver of the new energy automobile is that the new energy automobile is fast to accelerate, the discharge multiplying power is high due to the fact that the driver steps on the new energy automobile too fast, the service life of the battery is shortened, and if the driver slowly accelerates, the method is helpful for prolonging the service life of the battery of the new energy automobile.
Secondly, in order to prolong the service life of the battery, the battery is not charged until the electric quantity is less than 20%, the electric quantity is controlled between 25% and 75% as much as possible, the battery attenuation can be reduced, the service life of the battery is related to the cycle number, the cycle number is calculated from 0 electricity to full electricity once, and if the battery is full from 50%, the cycle number is calculated once after charging twice.
Again, if the vehicle is parked for a long time and not charged, the service life of the new energy battery is adversely affected, many new energy automobile users may use the vehicle frequently not very much, the vehicle is put for a few months or the battery is not charged at regular intervals, and of course, the situation that the electric load is overlarge is caused when the charging is not carried out for a long time, and the service life of the battery is reduced when the charging is carried out for a long time.
Finally, the temperature of the working environment of the new energy battery has great influence on the battery, the battery is not required to be driven or charged in the environment higher than 60 ℃, the heat dissipation of the battery is influenced by the excessively high temperature, the fire disaster is caused by more serious explosion, the new energy vehicle is not required to be charged when the temperature is lower than-5 ℃, and the battery can be self-protected when the temperature is too low.
Generally, when the maximum capacity of a ternary lithium battery is reduced to eighty percent of the maximum capacity in a factory state, the battery should be replaced. However, in actual use, people do not determine the number of remaining charge cycles between the current time and the time when the maximum capacity of the ternary lithium battery is reduced to eighty percent of the maximum capacity of the factory state, so that the battery replacement time cannot be effectively grasped.
Disclosure of Invention
In order to solve the technical problems in the related art, the invention provides a new energy automobile driving motor performance detection system, which can customize an artificial intelligent model to predict the number of remaining charging cycles from the current moment to the replacement of a battery by adopting the artificial intelligent model based on the latest starting parameters, the working temperature and the charge-discharge time length of a ternary lithium battery of a new energy automobile, thereby facilitating the control of the replacement time of the battery by a new energy automobile user and improving the intelligent level of battery management of the new energy automobile.
According to an aspect of the present invention, there is provided a new energy automobile driving motor performance detection system, the system comprising:
the starting detection device is arranged in the new energy automobile and is connected with an accelerator mechanism of the new energy automobile, and is used for detecting the stroke length of a pedal structure in unit time when a driver steps on the accelerator mechanism each time when starting, so as to obtain each stroke length corresponding to each starting in a set time length before the current moment, wherein each accelerator mechanism comprises the pedal structure;
the temperature measuring device is arranged in the new energy automobile and is used for measuring the average working temperature of the ternary lithium battery of the new energy automobile in a working state within a set time length before the current moment;
the charge-discharge analyzer is arranged in the new energy automobile and is used for acquiring the average value of each discharge time length of the ternary lithium battery in a set time length before the current moment to be used as a reference discharge average value and acquiring the average value of each charge time length of the ternary lithium battery in the set time length before the current moment to be used as a reference charge average value;
the frequency prediction mechanism is respectively connected with the starting detection device, the temperature measurement device and the charge-discharge analyzer, and is used for predicting the charge cycle frequency from the current moment to eighty percent of the maximum battery capacity of the ternary lithium battery in the ternary lithium battery delivery state based on an artificial intelligent model according to the stroke length, the average working temperature, the reference discharge mean value, the reference charge mean value, the maximum battery capacity of the ternary lithium battery delivery state and the maximum battery capacity of the ternary lithium battery in the current moment, which are respectively corresponding to each starting in a set time length before the current moment, and outputting the charge cycle frequency as a predicted residual cycle frequency;
the replacement notification mechanism is connected with the frequency prediction mechanism and is used for sending a replacement notification signal when the accumulated number of charge cycles of the ternary lithium battery reaches the predicted remaining number of cycles after the current moment;
and the replacement notification mechanism is also used for sending out a continuous use signal when the accumulated number of times of completing charging cycle of the ternary lithium battery after the current moment does not reach the predicted remaining number of times.
It can be seen that the present invention needs to have at least the following important aspects:
firstly, predicting the number of charge cycles remained between the current moment and the replacement of the battery by adopting an artificial intelligent model based on the latest starting parameters, the working temperature and the charge-discharge time length of the ternary lithium battery of the new energy automobile, so as to provide key information for the replacement time of the new energy battery;
in the second step, in the detection of the latest starting parameters of the ternary lithium battery of the specific new energy automobile, the stroke length of the pedal structure in unit time when a driver steps on the accelerator mechanism every time when starting is detected, so that the stroke lengths corresponding to the starting times in the set time length before the current moment are obtained, and reliable data are provided for predicting the residual charging cycle times.
The new energy automobile driving motor performance detection system is compact in structure and intelligent in management. The method can intelligently predict the number of remaining charging cycles from the current moment to the replacement of the battery on the basis of customizing the artificial intelligent model, so that a new energy automobile user can conveniently control the replacement time of the battery, and the situation of excessive use of the battery is avoided.
Brief description of the drawings
Numerous advantages of the present invention may be better understood by those skilled in the art by reference to the accompanying drawings in which:
fig. 1 is a schematic structural view of a new energy automobile driving motor performance detection system according to a first embodiment of the present invention.
Fig. 2 is a schematic structural view of a new energy automobile driving motor performance detection system according to a second embodiment of the present invention.
Fig. 3 is a schematic structural view of a new energy automobile driving motor performance detection system according to a third embodiment of the present invention.
Detailed Description
Fig. 1 is a schematic structural view of a new energy automobile driving motor performance detection system according to a first embodiment of the present invention, the system including:
the starting detection device is arranged in the new energy automobile and is connected with an accelerator mechanism of the new energy automobile, and is used for detecting the stroke length of a pedal structure in unit time when a driver steps on the accelerator mechanism each time when starting, so as to obtain each stroke length corresponding to each starting in a set time length before the current moment, wherein each accelerator mechanism comprises the pedal structure;
the temperature measuring device is arranged in the new energy automobile and is used for measuring the average working temperature of the ternary lithium battery of the new energy automobile in a working state within a set time length before the current moment;
the charge-discharge analyzer is arranged in the new energy automobile and is used for acquiring the average value of each discharge time length of the ternary lithium battery in a set time length before the current moment to be used as a reference discharge average value and acquiring the average value of each charge time length of the ternary lithium battery in the set time length before the current moment to be used as a reference charge average value;
the frequency prediction mechanism is respectively connected with the starting detection device, the temperature measurement device and the charge-discharge analyzer, and is used for predicting the charge cycle frequency from the current moment to eighty percent of the maximum battery capacity of the ternary lithium battery in the ternary lithium battery delivery state based on an artificial intelligent model according to the stroke length, the average working temperature, the reference discharge mean value, the reference charge mean value, the maximum battery capacity of the ternary lithium battery delivery state and the maximum battery capacity of the ternary lithium battery in the current moment, which are respectively corresponding to each starting in a set time length before the current moment, and outputting the charge cycle frequency as a predicted residual cycle frequency;
the replacement notification mechanism is connected with the frequency prediction mechanism and is used for sending a replacement notification signal when the accumulated number of charge cycles of the ternary lithium battery reaches the predicted remaining number of cycles after the current moment;
and the replacement notification mechanism is also used for sending out a continuous use signal when the accumulated number of times of completing charging cycle of the ternary lithium battery after the current moment does not reach the predicted remaining number of times.
Fig. 2 is a schematic structural view of a new energy automobile driving motor performance detection system according to a second embodiment of the present invention.
Unlike fig. 1, the new energy vehicle driving motor performance detection system in fig. 2 may further include the following components:
the capacity detection mechanism is arranged in the new energy automobile, is connected with the frequency prediction mechanism and the ternary lithium battery respectively, and is used for detecting the maximum battery capacity of the ternary lithium battery at the current moment;
the capacity detection mechanism is further used for sending the maximum battery capacity of the ternary lithium battery at the current moment to the frequency prediction mechanism.
Fig. 3 is a schematic structural view of a new energy automobile driving motor performance detection system according to a third embodiment of the present invention.
Unlike fig. 1, the new energy vehicle driving motor performance detection system in fig. 3 may further include the following components:
the information storage mechanism is connected with the frequency prediction mechanism and is used for storing the maximum battery capacity of the delivery state of the ternary lithium battery;
the information storage mechanism is also used for sending the maximum battery capacity of the delivery state of the ternary lithium battery to the frequency prediction mechanism.
Next, a specific structure of the new energy automobile driving motor performance detection system of the present invention will be further described.
In the new energy automobile driving motor performance detection system according to various embodiments of the present invention:
according to each stroke length, average working temperature, reference discharge average value, reference charge average value, maximum battery capacity of the ternary lithium battery in the factory state and maximum battery capacity of the ternary lithium battery in the current time, which are respectively corresponding to each start in a set time length before the current time, predicting the charge cycle number from the current time to eighty percent future time when the maximum battery capacity of the ternary lithium battery is reduced to the maximum battery capacity of the ternary lithium battery in the factory state based on an artificial intelligence model, and outputting the charge cycle number as predicted residual cycle number, wherein the predicted residual cycle number comprises: the artificial intelligent model is a convolutional neural network for completing the learning of set times;
wherein, the artificial intelligence model is for accomplishing the convolutional neural network of setting for number of times study includes: the value of the set times is positively correlated with the maximum battery capacity of the ternary lithium battery in the factory state;
wherein predicting, based on an artificial intelligent model, a number of charge cycles between a current time and a future time when the maximum battery capacity of the ternary lithium battery drops to eighty percent of the maximum battery capacity of the ternary lithium battery in a factory state, and outputting the number of charge cycles as a predicted remaining cycle number, according to respective stroke lengths, average operating temperatures, reference discharge average values, reference charge average values, maximum battery capacities of the ternary lithium battery in a factory state, and the maximum battery capacities of the ternary lithium battery in the current time, which are respectively corresponding to respective starts within a set time length before the current time, each start being performed by a respective start time, wherein the artificial intelligent model comprises: taking the stroke length, the average working temperature, the reference discharge average value, the reference charge average value, the maximum battery capacity of the delivery state of the ternary lithium battery and the maximum battery capacity of the current time of the ternary lithium battery which are respectively corresponding to each start in a set time length before the current time as each input data of the artificial intelligent model;
wherein predicting, based on an artificial intelligent model, a number of charge cycles between a current time and a future time when the maximum battery capacity of the ternary lithium battery drops to eighty percent of the maximum battery capacity of the ternary lithium battery in a factory state, and outputting the number of charge cycles as a predicted remaining cycle number, according to respective stroke lengths, average operating temperatures, reference discharge average values, reference charge average values, maximum battery capacities of the ternary lithium battery in a factory state, and the maximum battery capacities of the ternary lithium battery in the current time, which are respectively corresponding to respective starts within a set time length before the current time, each start being performed by a respective start time, wherein the artificial intelligent model comprises: and the number of charging cycles from the current moment to the future moment when the maximum battery capacity of the ternary lithium battery is reduced to eighty percent of the maximum battery capacity of the ternary lithium battery in a factory state is single output data of the artificial intelligent model after the artificial intelligent model is operated.
In the new energy automobile driving motor performance detection system according to various embodiments of the present invention:
the method for measuring the average working temperature of the ternary lithium battery of the new energy automobile in the working state within the set time length before the current moment comprises the following steps: acquiring each time interval when a ternary lithium battery of a new energy automobile is in a working state within a set time length before the current moment, uniformly and time-sharing acquiring each working temperature in each time interval, performing average value calculation to acquire a reference average value temperature corresponding to the time drive, and taking an arithmetic average value of each reference average value temperature of each time interval to acquire the average working temperature;
wherein, evenly and time-sharing obtaining each working temperature in each time interval and carrying out average calculation to obtain a reference average temperature corresponding to the time drive, and arithmetic average of each reference average temperature in each time interval to obtain the average working temperature comprises the following steps: the operating temperature is the surface temperature of the ternary lithium battery.
And in the new energy automobile driving motor performance detection system according to various embodiments of the present invention:
the charge-discharge analyzer comprises first analysis equipment, a first analysis module and a second analysis module, wherein the first analysis equipment is used for acquiring the average value of each discharge duration of the ternary lithium battery in a set time length before the current moment to serve as a reference discharge average value;
the charge-discharge analyzer further comprises second analysis equipment, and the second analysis equipment is used for acquiring the average value of each charging duration of the ternary lithium battery in a set time length before the current moment to serve as a reference charging average value.
In addition, in the new energy automobile driving motor performance detection system, the stroke length of the pedal structure in unit time when a driver steps on the accelerator mechanism each time when starting is detected, so as to obtain each stroke length corresponding to each starting in a set time length before the current moment, wherein each accelerator mechanism comprises the pedal structure and comprises: the set time length takes a value between 30 days and 100 days.
Various features of the invention have been described in detail in connection with various embodiments. It is to be understood that this specific description is by way of example only and that the invention is best explained by the scope of the appended claims.

Claims (10)

1. A new energy automobile driving motor performance detection system, characterized in that the system comprises:
the starting detection device is arranged in the new energy automobile and is connected with an accelerator mechanism of the new energy automobile, and is used for detecting the stroke length of a pedal structure in unit time when a driver steps on the accelerator mechanism each time when starting, so as to obtain each stroke length corresponding to each starting in a set time length before the current moment, wherein each accelerator mechanism comprises the pedal structure;
the temperature measuring device is arranged in the new energy automobile and is used for measuring the average working temperature of the ternary lithium battery of the new energy automobile in a working state within a set time length before the current moment;
the charge-discharge analyzer is arranged in the new energy automobile and is used for acquiring the average value of each discharge time length of the ternary lithium battery in a set time length before the current moment to be used as a reference discharge average value and acquiring the average value of each charge time length of the ternary lithium battery in the set time length before the current moment to be used as a reference charge average value;
the frequency prediction mechanism is respectively connected with the starting detection device, the temperature measurement device and the charge-discharge analyzer, and is used for predicting the charge cycle frequency from the current moment to eighty percent of the maximum battery capacity of the ternary lithium battery in the ternary lithium battery delivery state based on an artificial intelligent model according to the stroke length, the average working temperature, the reference discharge mean value, the reference charge mean value, the maximum battery capacity of the ternary lithium battery delivery state and the maximum battery capacity of the ternary lithium battery in the current moment, which are respectively corresponding to each starting in a set time length before the current moment, and outputting the charge cycle frequency as a predicted residual cycle frequency;
the replacement notification mechanism is connected with the frequency prediction mechanism and is used for sending a replacement notification signal when the accumulated number of charge cycles of the ternary lithium battery reaches the predicted remaining number of cycles after the current moment;
and the replacement notification mechanism is also used for sending out a continuous use signal when the accumulated number of times of completing charging cycle of the ternary lithium battery after the current moment does not reach the predicted remaining number of times.
2. The new energy automobile driving motor performance detection system according to claim 1, wherein the system further comprises:
the capacity detection mechanism is arranged in the new energy automobile, is connected with the frequency prediction mechanism and the ternary lithium battery respectively, and is used for detecting the maximum battery capacity of the ternary lithium battery at the current moment;
the capacity detection mechanism is further used for sending the maximum battery capacity of the ternary lithium battery at the current moment to the frequency prediction mechanism.
3. The new energy automobile driving motor performance detection system according to claim 1, wherein the system further comprises:
the information storage mechanism is connected with the frequency prediction mechanism and is used for storing the maximum battery capacity of the delivery state of the ternary lithium battery;
the information storage mechanism is also used for sending the maximum battery capacity of the delivery state of the ternary lithium battery to the frequency prediction mechanism.
4. A new energy automobile driving motor performance detection system according to any one of claims 1-3, wherein:
according to each stroke length, average working temperature, reference discharge average value, reference charge average value, maximum battery capacity of the ternary lithium battery in the factory state and maximum battery capacity of the ternary lithium battery in the current time, which are respectively corresponding to each start in a set time length before the current time, predicting the charge cycle number from the current time to eighty percent future time when the maximum battery capacity of the ternary lithium battery is reduced to the maximum battery capacity of the ternary lithium battery in the factory state based on an artificial intelligence model, and outputting the charge cycle number as predicted residual cycle number, wherein the predicted residual cycle number comprises: the artificial intelligent model is a convolutional neural network for completing set times of learning.
5. The new energy automobile driving motor performance detection system according to claim 4, wherein:
the convolutional neural network for completing the set times of learning by the artificial intelligence model comprises: and the value of the set times is positively correlated with the maximum battery capacity of the ternary lithium battery in the factory state.
6. The new energy automobile driving motor performance detection system according to claim 5, wherein:
according to each stroke length, average working temperature, reference discharge average value, reference charge average value, maximum battery capacity of the ternary lithium battery in the factory state and maximum battery capacity of the ternary lithium battery in the current time, which are respectively corresponding to each start in a set time length before the current time, predicting the charge cycle number from the current time to eighty percent future time when the maximum battery capacity of the ternary lithium battery is reduced to the maximum battery capacity of the ternary lithium battery in the factory state based on an artificial intelligence model, and outputting the charge cycle number as predicted residual cycle number, wherein the predicted residual cycle number comprises: and taking the stroke length, the average working temperature, the reference discharge average value, the reference charge average value, the maximum battery capacity of the delivery state of the ternary lithium battery and the maximum battery capacity of the current moment of the ternary lithium battery which are respectively corresponding to each start in a set time length before the current moment as each input data of the artificial intelligent model.
7. The new energy automobile driving motor performance detection system according to claim 6, wherein:
according to each stroke length, average working temperature, reference discharge average value, reference charge average value, maximum battery capacity of the ternary lithium battery in the factory state and maximum battery capacity of the ternary lithium battery in the current time, which are respectively corresponding to each start in a set time length before the current time, predicting the charge cycle number from the current time to eighty percent future time when the maximum battery capacity of the ternary lithium battery is reduced to the maximum battery capacity of the ternary lithium battery in the factory state based on an artificial intelligence model, and outputting the charge cycle number as predicted residual cycle number, wherein the predicted residual cycle number comprises: and the number of charging cycles from the current moment to the future moment when the maximum battery capacity of the ternary lithium battery is reduced to eighty percent of the maximum battery capacity of the ternary lithium battery in a factory state is single output data of the artificial intelligent model after the artificial intelligent model is operated.
8. A new energy automobile driving motor performance detection system according to any one of claims 1-3, wherein:
the method for measuring the average working temperature of the ternary lithium battery of the new energy automobile in the working state within the set time length before the current moment comprises the following steps: and acquiring each time interval when the ternary lithium battery of the new energy automobile is in a working state within a set time length before the current time, uniformly and time-sharing each working temperature in each time interval, carrying out mean value calculation to obtain a reference mean value temperature corresponding to the time drive, and taking an arithmetic mean value of each reference mean value temperature of each time interval to obtain the average working temperature.
9. The new energy automobile driving motor performance detection system of claim 8, wherein:
evenly and time-sharing each working temperature in each time interval, carrying out average calculation to obtain a reference average temperature corresponding to the time drive, and carrying out arithmetic average on each reference average temperature in each time interval to obtain the average working temperature, wherein the steps comprise: the operating temperature is the surface temperature of the ternary lithium battery.
10. A new energy automobile driving motor performance detection system according to any one of claims 1-3, wherein:
the charge-discharge analyzer comprises first analysis equipment, a first analysis module and a second analysis module, wherein the first analysis equipment is used for acquiring the average value of each discharge duration of the ternary lithium battery in a set time length before the current moment to serve as a reference discharge average value;
the charge-discharge analyzer further comprises second analysis equipment, and the second analysis equipment is used for acquiring the average value of each charging duration of the ternary lithium battery in a set time length before the current moment to serve as a reference charging average value.
CN202310220195.XA 2023-03-09 2023-03-09 New energy automobile driving motor performance detecting system Withdrawn CN116184219A (en)

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CN202310220195.XA CN116184219A (en) 2023-03-09 2023-03-09 New energy automobile driving motor performance detecting system

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Application Number Priority Date Filing Date Title
CN202310220195.XA CN116184219A (en) 2023-03-09 2023-03-09 New energy automobile driving motor performance detecting system

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