Electric drive system fault early warning method and system

Abstract

The invention discloses an electric driving system fault early warning method and system, relates to the technical field of electric driving system detection, solves the technical problem that in the prior art, running characteristic diagnosis cannot be carried out on a tire when an electric driving system is in a supply stage, and specifically, the electric driving system supplies energy to the tire after entering the supply stage; analyzing and diagnosing tire running characteristics in the energy supply process, marking the tire as a direct supply object, collecting tire energy supply characteristic information, obtaining an energy supply characteristic diagnosis coefficient according to calculation, constructing a curve according to the coefficient, setting a threshold value, and constructing a parameter boundary; dividing the tire into a tire high-efficiency section and a tire low-efficiency section through a parameter boundary, and analyzing and deducing whether the energy supply characteristics of the tire are qualified or not through corresponding types of time periods.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of electric drive system detection, in particular to an electric drive system fault early warning method and system. BACKGROUND

[0002] The electric drive system is the core power system of electric vehicles, electric ships, electric aircraft and many industrial devices; electric drive system fault early warning is a key technology that can detect potential problems in the electric drive system in advance to avoid or reduce the damage caused by the failure.

[0003] However, in the prior art, the electric drive system is in the supply stage, and cannot perform battery characteristic diagnosis, and cannot perform operating environment detection, so that the electric energy supply efficiency is reduced, and in addition, the tire operating characteristic diagnosis cannot be performed in the supply stage of the electric drive system, and the energy supply detection accuracy is reduced.

[0004] In view of the above technical defects, a solution is proposed. SUMMARY

[0005] The purpose of the present application is to solve the above-mentioned problems, and to provide an electric drive system fault early warning method and system.

[0006] The purpose of the present application can be achieved by the following technical solutions: An electric drive system fault early warning method, the fault early warning method process is as follows: Battery characteristic diagnosis, battery characteristic diagnosis is performed in the supply stage, the supply performance of the battery pack inside the electric drive system is detected in real time through battery characteristic diagnosis, battery characteristic diagnosis information is collected, and a characteristic diagnosis coefficient is obtained through calculation, whether the characteristic diagnosis of the energy storage main body is abnormal is inferred according to the coefficient, yes, characteristic early warning is performed, no, the next step is performed; Running environment control characteristic diagnosis, after the battery characteristic diagnosis is qualified, the battery running energy supply environment in the electric drive system and the influence of environmental control are analyzed synchronously, the influence information of the ring temperature and the influence information of the ring speed are collected, whether the running environment characteristic diagnosis of the electric drive system is abnormal is inferred according to the information, yes, parameter control is performed, no, the next step is performed; Tire energy supply characteristic diagnosis, after entering the supply stage, the electric drive system supplies energy to the tire, analyzes and diagnoses the tire operating characteristics in the energy supply process, and marks the tire as a direct supply object, collects tire energy supply characteristic information, and obtains an energy supply characteristic diagnosis coefficient according to calculation, constructs a curve according to the coefficient and sets a threshold to construct a parameter boundary line, and divides the tire into a tire high efficiency section and a tire low efficiency section through the parameter boundary line, and whether the tire energy supply characteristic is qualified is inferred through corresponding type period analysis; The energy supply efficiency characteristic diagnosis is performed, and after the tire energy supply of the electric drive system is qualified and the characteristic diagnosis is qualified, the energy supply efficiency characteristic analysis diagnosis is performed, the supply stall data and the supply delay data are collected, and whether the energy supply efficiency characteristic diagnosis of the electric drive system is abnormal is inferred according to data analysis.

[0007] As a preferred embodiment of the present application, the battery characteristic diagnosis information includes the maximum interval duration increase span of adjacent period charging and discharging, the charging speed floating deviation of each energy storage module in the energy storage main body at different charging temperatures, and the maximum deviation value of the power remaining amount of any amount of energy storage modules in the energy storage main body at the real-time discharging speed in the discharging stage.

[0008] As a preferred embodiment of the present application, if the characteristic diagnosis coefficient exceeds the characteristic diagnosis coefficient threshold value, it is inferred that the characteristic diagnosis of the energy storage main body is abnormal; if the characteristic diagnosis coefficient does not exceed the characteristic diagnosis coefficient threshold value, it is inferred that the characteristic diagnosis of the energy storage main body is normal.

[0009] As a preferred embodiment of the present application, the ambient temperature influence information and the ambient speed influence information are respectively the real-time charging temperature rise span peak value and the temperature rise stage energy storage main body capacity floating span corresponding cumulative sum, and the speed deviation time point total number proportion of the real-time charging port power supply speed and the energy storage main body power filling speed corresponding to the charging temperature rise stage. If the ambient temperature influence information exceeds the span cumulative sum threshold value, or the ambient speed influence information exceeds the time point number proportion threshold value, an ambient control characteristic abnormal signal is generated; if the ambient temperature influence information does not exceed the span cumulative sum threshold value, and the ambient speed influence information does not exceed the time point number proportion threshold value, an ambient control characteristic normal signal is generated.

[0010] As a preferred embodiment of the present application, the tire energy supply characteristic information includes the speed deviation value of the rubber tire rotation speed and the wheel shaft center rotation speed in the direct supply object, and the number increase span of the wheel rotation at the same position when the direct supply object appears the speed deviation value. The energy supply characteristic diagnosis coefficient of the direct supply object is counted in the new energy electric vehicle driving period, and the coefficient curve is constructed according to each time point, the parameter boundary line is obtained according to the coefficient threshold value, and the coefficient curve is divided into a tire high efficiency section and a tire low efficiency section according to the parameter boundary line.

[0011] As a preferred embodiment of the present application, the high floating data and the high stable data are collected, and the high floating data and the high stable data are respectively the maximum value of the floating span corresponding to the curve when the electric vehicle starts in the tire high efficiency section, and the average value of the reciprocating floating span of the curve at any driving time point in the tire high efficiency section. If the high-float data exceeds the peak threshold of the down-float span or the high-stable data exceeds the mean threshold of the reciprocating span, the current tire efficient section is determined as an efficient unstable section; if the high-float data does not exceed the peak threshold of the down-float span and the high-stable data does not exceed the mean threshold of the reciprocating span, the current tire efficient section is determined as an efficient stable section.

[0012] As a preferred embodiment of the present application, low uniform float data and low reduced float data are collected, and the low uniform float data and the low reduced float data are respectively the curve float frequency corresponding to the uniform speed driving period of the electric vehicle in the tire inefficient section and the down-float span increase frequency corresponding to the deceleration driving period of the electric vehicle; If the low uniform float data exceeds the float frequency threshold or the low reduced float data exceeds the down-float span increase frequency threshold, the current tire inefficient section is determined as an inefficient unstable section; if the low uniform float data does not exceed the float frequency threshold and the low reduced float data does not exceed the down-float span increase frequency threshold, the current tire inefficient section is determined as an inefficient stable section.

[0013] As a preferred embodiment of the present application, the driving period of the electric vehicle is analyzed for the period type, and if the cumulative length ratio of the efficient stable section and the inefficient stable section exceeds the cumulative length ratio threshold, it is inferred that the current electric drive system tire energy supply is qualified; If the length ratio of the inefficient unstable section exceeds the inefficient length ratio threshold, it is inferred that the current electric drive system tire energy supply is inefficient; if the length ratio of the efficient unstable section exceeds the efficient length ratio threshold, it is inferred that the current electric drive system tire energy supply is abnormal.

[0014] As a preferred embodiment of the present application, the supply stall data and the supply delay data are respectively the vehicle speed float value caused by the power supply amount decrease of the electric drive system supply stage when the electric vehicle drives without float, and the energy supply change delay span when the electric vehicle drives with speed float in the electric drive system supply stage; If the supply stall data exceeds the speed float threshold or the supply delay data exceeds the supply delay threshold, a dangerous energy supply signal is generated; if the supply stall data does not exceed the speed float threshold and the supply delay data does not exceed the supply delay threshold, a normal energy supply signal is generated.

[0015] An electric drive system fault early warning system, comprising a battery characteristic diagnosis unit, an operation ring control characteristic diagnosis unit, a tire energy supply characteristic diagnosis unit, and an energy supply efficiency characteristic diagnosis unit; The battery characteristic diagnosis unit performs battery characteristic diagnosis in the supply stage, detects the supply performance of the battery pack inside the electric drive system in real time through the battery characteristic diagnosis, collects battery characteristic diagnosis information, and obtains a characteristic diagnosis coefficient through calculation, and infers whether the characteristic diagnosis of the energy storage main body is abnormal according to the coefficient comparison; The battery characteristic diagnosis unit is started, and after the battery characteristic diagnosis is qualified, the running environment of the battery in the electric drive system and the influence of the environment control are synchronously analyzed, the influence information of the ambient temperature and the influence information of the ambient speed are collected, and whether the environment characteristic diagnosis of the electric drive system is abnormal is inferred according to information comparison; The tire energy supply characteristic diagnosis unit is started, the tire is supplied with energy by the electric drive system after entering the supply stage, the running characteristics of the tire in the energy supply process are analyzed and diagnosed, the tire is marked as a direct supply object, the tire energy supply characteristic information is collected, the energy supply characteristic diagnosis coefficient is obtained according to calculation, the curve is constructed according to the coefficient, the threshold value is set to construct the parameter demarcation line, and the tire is divided into a tire high-efficiency section and a tire low-efficiency section through the parameter demarcation line, and whether the tire energy supply characteristic is qualified is inferred through corresponding type period analysis. The energy supply efficiency characteristic diagnosis unit is started, the energy supply efficiency characteristic is analyzed and diagnosed after the tire energy supply of the electric drive system is completed and the characteristic diagnosis is qualified, the supply stall data and the supply delay data are collected, and whether the energy supply efficiency characteristic diagnosis of the electric drive system is abnormal is inferred according to data analysis.

[0016] Compared with the prior art, the beneficial effects of the present application are: 1、In the present application, the supply performance of the battery pack in the electric drive system is detected in real time through the battery characteristic diagnosis, so that the performance of the internal battery pack is prevented from being abnormal, the overall supply efficiency of the electric drive system is prevented from being reduced, and the supply environment is prevented from being continuously deteriorated due to the performance abnormality of the battery pack, so as to further reduce the supply efficiency of the electric drive system, and the hardware loss in the electric drive system is increased in this cycle, and the natural running life of the electric drive system is reduced. The running environment of the battery in the electric drive system and the influence of the environment control are synchronously analyzed, whether there is an influence of the running environment in the subsequent running process when the performance of the battery pack is qualified is inferred in turn, so that the supply capacity of the electric drive system is reduced, and the running influence parameters of the battery pack are also generated, so that the supply balance of the battery pack is broken, and the electric energy supply cannot be efficiently performed.

[0017] 2、In the present application, the running characteristics of the tire in the energy supply process are analyzed and diagnosed, whether the current energy supply meets the tire running is inferred according to the tire characteristic analysis, the tire is prevented from being driven in the current scene due to the energy supply, the overall supply efficiency of the electric drive system is prevented from being reduced, the running efficiency and stability of the new energy electric vehicle in which the electric drive system is located are prevented from being affected, and the running environment of the tire is also prevented from being in a poor state, and unnecessary tire wear is generated. In the present application, the real-time energy supply efficiency is analyzed during the energy supply process of the new energy electric vehicle by the electric drive system, whether the energy supply efficiency is abnormal is inferred through the energy supply efficiency analysis at each moment, so that the energy supply is adjusted in time when the energy supply efficiency is abnormal, and the driving risk is prevented from being increased due to the supply abnormality when the new energy electric vehicle runs. BRIEF DESCRIPTION OF DRAWINGS

[0018] For the convenience of those skilled in the art to understand, the present application will be further described below in conjunction with the drawings.

[0019] Figure 1 The method flowchart of the present application; Figure 2 The system principle block diagram of the present application. DETAILED DESCRIPTION

[0020] In order to make the person skilled in the art better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0021] In this paper, the "embodiment" means that the specific features, structures or characteristics described in conjunction with the embodiment can be included in at least one embodiment of the present application. The phrase appears at various places in the specification does not necessarily refer to the same embodiment, nor is it independent or alternative to other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0022] Please refer to Figure 1 As shown in the figure, a fault early warning method of electric drive system, the specific fault early warning method process is as follows: The electric drive system starts, and the electric drive system is the energy source of new energy electric car. In the actual energy supply process, it is divided into electric drive supply stage and electric drive supply stage. The electric drive supply stage means that the internal battery of the electric drive supplies power, so that the electric drive system generates supplyable electric energy. The electric drive supply stage means that the electric drive generates supplyable electric energy to drive the new energy electric car. The specific direct energy supply corresponds to the tire. Battery characteristic diagnosis, battery characteristic diagnosis is carried out in the supply stage. Through the real-time detection of the supply performance of the internal battery pack of the electric drive system by the battery characteristic diagnosis, the performance abnormality of the internal battery pack is avoided, which causes the overall supply efficiency of the electric drive system to decrease. The performance abnormality of the battery pack makes the supply environment continue to deteriorate, so as to further reduce the supply efficiency of the electric drive system. The cycle increase of the hardware loss in the electric drive system reduces the natural operation life of the electric drive system; The running environment control feature diagnosis is performed in the supply stage. After the battery feature diagnosis is qualified, the running supply environment of the battery in the electric drive system and the environmental control influence are analyzed synchronously. It is inferred in turn whether there is an operating environment influence in the subsequent running process when the battery pack performance is qualified. Therefore, the supply capacity of the electric drive system is reduced, and the battery pack running influence parameter is also generated. Therefore, the battery pack supply balance is broken, and the electric energy supply cannot be efficiently performed. The tire supply feature diagnosis is performed in the supply stage. The electric drive system supplies energy to the tire, and analyzes and diagnoses the tire running features during the energy supply process. Whether the current energy supply meets the tire running is inferred according to the tire feature analysis. The tire is prevented from driving in the current scene due to the inability of the energy supply. Therefore, the overall supply efficiency of the electric drive system is reduced, the running efficiency and stability of the new energy electric vehicle in which the electric drive system is located are affected, and the running environment of the tire is in a poor state, causing unnecessary tire wear. The energy supply efficiency feature diagnosis is performed after the tire energy supply of the electric drive system is completed and the feature diagnosis is qualified. The real-time energy supply efficiency is analyzed during the energy supply process of the new energy electric vehicle in the electric drive system. Whether the energy supply efficiency is abnormal is inferred through the energy supply efficiency analysis at each time. Therefore, the energy supply is adjusted in time when the energy supply efficiency is abnormal. The driving risk is avoided due to the supply abnormality of the new energy electric vehicle during running. The battery feature diagnosis process is as follows: The battery pack in the electric drive system is set as the energy storage main body. The maximum interval time span increase of adjacent cycles of the energy storage main body during the charge and discharge cycle is obtained, and the maximum interval time span increase of adjacent cycles of the energy storage main body during the charge and discharge cycle is marked as ZKD. It can be understood that the adjacent cycles correspond to the use-up or fullness of the electric quantity. Therefore, there is a risk of excessive depletion or overcharging. The charge speed floating deviation of each energy storage module in the energy storage main body at different charge temperatures during the charge stage in the energy storage main body during the charge and discharge cycle is obtained, and the charge speed floating deviation of each energy storage module in the energy storage main body at different charge temperatures during the charge stage in the energy storage main body during the charge and discharge cycle is marked as FDP. It can be understood that the energy storage module is a module for storing electric quantity in the energy storage main body, such as a plurality of sub-batteries in the battery pack. If the charge speed of the corresponding sub-battery at different temperatures deviates too much, the adaptation speed of the corresponding battery charge at the corresponding charge stage is different, which easily causes the performance difference between the sub-batteries to increase. The maximum deviation value of the remaining electric quantity of the arbitrary amount of energy storage modules of the energy storage main body at the real-time discharge speed in the discharge stage of the energy storage main body charging and discharging cycle is obtained, and the maximum deviation value of the remaining electric quantity of the arbitrary amount of energy storage modules of the energy storage main body at the real-time discharge speed in the discharge stage of the energy storage main body charging and discharging cycle is marked as ZDP; it can be understood that if the real-time electric quantity deviation of the energy storage modules in the energy storage main body is too large, the corresponding energy storage module is not suitable for combination, which is easy to cause overcharging or overdischarging of the energy storage module; The above collected information is uniformly marked as battery characteristic diagnosis information, and the characteristic diagnosis coefficient of the energy storage main body is obtained by substituting the formula: , G is the characteristic diagnosis coefficient, axz1, axz2 and axz3 are respectively preset proportion coefficients, and β is an error correction factor, and the value is 0.97; The characteristic diagnosis coefficient of the energy storage main body is compared with the characteristic diagnosis coefficient threshold value: If the characteristic diagnosis coefficient of the energy storage main body exceeds the characteristic diagnosis coefficient threshold value, it is inferred that the characteristic diagnosis of the energy storage main body is abnormal, the battery characteristic warning is carried out, the system marks the corresponding energy storage module of the energy storage main body and gives a warning, and the administrator carries out hardware control of the electric drive system; If the characteristic diagnosis coefficient of the energy storage main body does not exceed the characteristic diagnosis coefficient threshold value, it is inferred that the characteristic diagnosis of the energy storage main body is normal; The operation of the environmental control characteristic diagnosis process is as follows: The real-time charging temperature rising span peak value and the capacity floating span corresponding value cumulative sum of the energy storage main body in the temperature rising stage during the charging process of the electric drive system are obtained, wherein the value cumulative sum only carries out addition calculation on the value of the data, and the value floating influence is obtained, without considering the unit of the data; and the real-time charging temperature rising span peak value and the capacity floating span corresponding value cumulative sum of the energy storage main body in the temperature rising stage during the charging process of the electric drive system are marked as the influence information of the ring temperature; The total number of speed deviation time points corresponding to the real-time charging port power supply speed and the energy storage main body electric quantity filling speed in the charging temperature rising stage during the charging process of the electric drive system is obtained, and the total proportion of the speed deviation time points in the charging time is obtained, which reflects whether the charging environment influence exists, and the total number of speed deviation time points corresponding to the real-time charging port power supply speed and the energy storage main body electric quantity filling speed in the charging temperature rising stage during the charging process of the electric drive system is marked as the influence information of the ring speed; And respectively with the span cumulative sum threshold value and the time point number proportion threshold value are compared: If the ambient temperature influence information exceeds the span accumulation threshold value or the ambient speed influence information exceeds the time point proportion threshold value, it is inferred that the electric drive system operating environment feature diagnosis is abnormal, an environmental control feature abnormal signal is generated and sent to the administrator terminal, and after the administrator terminal receives the environmental control feature abnormal signal, the charging environment parameters of the electric drive system are regulated, such as temperature regulation and real-time charging speed regulation. If the ambient temperature influence information does not exceed the span accumulation threshold value, and the ambient speed influence information does not exceed the time point proportion threshold value, it is inferred that the electric drive system operating environment feature diagnosis is normal, an environmental control feature normal signal is generated and sent to the administrator terminal. The tire energy supply feature diagnosis process is as follows: After the electric drive system completes the supply stage, it enters the electric drive supply stage and marks the tire as a direct supply object. During the acceleration or braking process in the electric drive supply stage, the speed deviation value of the rubber tire rotation speed and the wheel shaft center rotation speed in the direct supply object is obtained. At the same time, the number of revolutions of the wheel at the same position when the speed deviation value of the direct supply object appears increases the span, which reflects the influence of the wheel rotation number. The speed deviation value of the rubber tire rotation speed and the wheel shaft center rotation speed in the direct supply object, and the number of revolutions of the wheel at the same position when the speed deviation value of the direct supply object appears increase the span, are marked as SP and QZ, respectively. The above information is uniformly marked as tire energy supply feature information, and the energy supply feature diagnosis coefficient of the direct supply object is obtained by substituting the formula, wherein the formula is: wherein g1 and g2 are the preset proportion coefficients of the speed deviation value and the number of revolutions increase span, respectively, and a is the error correction factor. When the tire passes through the sandstone road or the rainwater road, the value is 0.89. When the tire passes through the sandstone road or the rainwater road, the value is 1.3. In the present application, sandstone road and rainwater road are taken as reference, and the error correction factor of the existing technology affecting tire slip is 0.89. The energy supply feature diagnosis coefficient of the direct supply object is counted during the new energy electric vehicle driving period, and the coefficient curve is constructed according to each time point. According to the coefficient threshold value, the parameter boundary line is obtained, and the coefficient curve is divided into tire high efficiency section and tire low efficiency section according to the parameter boundary line. The maximum value of the floating span of the curve corresponding to the starting period of the electric vehicle in the tire efficient section is obtained, and the average value of the reciprocating floating span of the curve corresponding to any driving moment in the tire efficient section is collected, wherein the span is represented as the vertical interval distance of the curve points corresponding to adjacent moments, such as the Y-axis interval distance of two points in the prior art curve; and the maximum value of the floating span of the curve corresponding to the starting period of the electric vehicle in the tire efficient section and the average value of the reciprocating floating span of the curve corresponding to any driving moment in the tire efficient section are marked as high floating data and high stability data respectively, and are compared with the floating span peak threshold value and the reciprocating span average threshold value respectively: If the maximum value of the floating span of the curve corresponding to the starting period of the electric vehicle in the tire efficient section exceeds the floating span peak threshold value, or the average value of the reciprocating floating span of the curve corresponding to any driving moment in the tire efficient section exceeds the reciprocating span average threshold value, the current tire efficient section is determined as an efficient unstable section; If the maximum value of the floating span of the curve corresponding to the starting period of the electric vehicle in the tire efficient section does not exceed the floating span peak threshold value, and the average value of the reciprocating floating span of the curve corresponding to any driving moment in the tire efficient section does not exceed the reciprocating span average threshold value, the current tire efficient section is determined as an efficient stable section; The floating frequency of the curve corresponding to the uniform speed driving period of the electric vehicle in the tire inefficient section and the increasing frequency of the floating span of the curve corresponding to the deceleration driving period of the electric vehicle are collected, and the floating frequency of the curve corresponding to the uniform speed driving period of the electric vehicle in the tire inefficient section and the increasing frequency of the floating span of the curve corresponding to the deceleration driving period of the electric vehicle are marked as low uniform floating data and low deceleration floating data respectively, and are compared with the floating frequency threshold value and the increasing frequency of the floating span threshold value respectively: If the floating frequency of the curve corresponding to the uniform speed driving period of the electric vehicle in the tire inefficient section exceeds the floating frequency threshold value, or the increasing frequency of the floating span of the curve corresponding to the deceleration driving period of the electric vehicle exceeds the increasing frequency of the floating span threshold value, the current tire inefficient section is determined as a low efficient unstable section; If the floating frequency of the curve corresponding to the uniform speed driving period of the electric vehicle in the tire inefficient section does not exceed the floating frequency threshold value, and the increasing frequency of the floating span of the curve corresponding to the deceleration driving period of the electric vehicle does not exceed the increasing frequency of the floating span threshold value, the current tire inefficient section is determined as a low efficient stable section; The driving period of the electric vehicle is analyzed, and if the cumulative time length ratio of the efficient stable section and the low efficient stable section exceeds the cumulative time length ratio threshold value, it is inferred that the current electric drive system tire energy supply is qualified; If the time length ratio of the low efficient unstable section exceeds the low efficient time length ratio threshold value, it is inferred that the current electric drive system tire energy supply is inefficient, and the electric drive system energy supply is controlled, that is, the rotation of the corresponding transmission shaft of the motor is improved by increasing the electric quantity supply; If the time length ratio of the efficient unstable section exceeds the efficient time length ratio threshold value, it is inferred that the current electric drive system tire energy supply is abnormal, and the electric drive system energy supply is maintained and the motor operation is detected; The technical scheme is aimed at the power supply of the electric drive system and the transmission of the tire. Whether the power supply is qualified is inferred through the power supply transmission shaft and the rotation speed deviation of the tire. In the analysis process, the high-efficiency section and the low-efficiency section are divided to reduce the influence of the power supply caused by the start of the electric vehicle when the electric vehicle is driving; The power supply efficiency feature diagnosis process is as follows: The vehicle speed floating value caused by the power supply decrease of the electric vehicle when the electric vehicle is driving without floating in the power supply stage of the electric drive system is obtained, and the power supply change delay span when the electric vehicle is driving with speed floating in the power supply stage of the electric drive system is obtained. The vehicle speed floating value caused by the power supply decrease of the electric vehicle when the electric vehicle is driving without floating in the power supply stage of the electric drive system is marked as supply stall data, and the power supply change delay span when the electric vehicle is driving with speed floating in the power supply stage of the electric drive system is marked as supply delay data. The two values are compared with the speed floating threshold and the supply delay threshold, respectively. If the vehicle speed floating value caused by the power supply decrease of the electric vehicle when the electric vehicle is driving without floating in the power supply stage of the electric drive system exceeds the speed floating threshold, or the power supply change delay span when the electric vehicle is driving with speed floating in the power supply stage of the electric drive system exceeds the supply delay threshold, it is inferred that the power supply efficiency feature diagnosis of the electric drive system is abnormal. A power supply danger signal is generated and sent to the administrator. After receiving the power supply danger signal, the administrator stops the power supply of the electric drive system and performs a comprehensive overhaul. If the vehicle speed floating value caused by the power supply decrease of the electric vehicle when the electric vehicle is driving without floating in the power supply stage of the electric drive system does not exceed the speed floating threshold, and the power supply change delay span when the electric vehicle is driving with speed floating in the power supply stage of the electric drive system does not exceed the supply delay threshold, it is inferred that the power supply efficiency feature diagnosis of the electric drive system is normal. A power supply normal signal is generated and sent to the administrator. Driving without floating means that the current driving road has no slope, pit, and no vehicle speed floating driving state. The running jitter and speed floating of the electric vehicle are set within a threshold range. If they are within the range, they are determined to be driving without floating. Please refer to Figure 2 The electric drive system fault early warning system includes a battery feature diagnosis unit, a running environment control feature diagnosis unit, a tire power supply feature diagnosis unit, and a power supply efficiency feature diagnosis unit. The battery feature diagnosis unit performs battery feature diagnosis in the supply stage. The supply performance of the battery pack in the electric drive system is detected in real time through battery feature diagnosis. Battery feature diagnosis information is collected, and a feature diagnosis coefficient is obtained through calculation. Whether the feature diagnosis of the energy storage main body is abnormal is inferred according to the coefficient comparison. The running environment control feature diagnosis unit synchronously analyzes the battery running power supply environment and the influence of environmental control in the electric drive system after the battery feature diagnosis is qualified. Ring temperature influence information and ring speed influence information are collected. Whether the electric drive system running environment feature diagnosis is abnormal is inferred according to the information comparison. The tire energy supply feature diagnosis unit analyzes and diagnoses the tire running features during the energy supply process after the tire enters the supply stage, and marks the tire as a direct supply object, collects tire energy supply feature information, and obtains an energy supply feature diagnosis coefficient according to the calculation, constructs a curve according to the coefficient, sets a threshold to construct a parameter boundary line, and divides the tire into a high-efficiency section and a low-efficiency section through the parameter boundary line, and analyzes and infers whether the tire energy supply feature is qualified through the corresponding type period; The energy supply efficiency feature diagnosis unit analyzes and diagnoses the energy supply efficiency features after completing the tire energy supply of the electric drive system and passing the feature diagnosis, collects supply stall data and supply delay data, and analyzes and infers whether the energy supply efficiency feature diagnosis of the electric drive system is abnormal according to the data.

[0023] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula close to the true value, and the coefficients in the formula are set by a person skilled in the art according to the actual situation; The preferred embodiments of the application disclosed above are only used to help explain the application. The preferred embodiments do not describe all the details and limit the application to the specific embodiments. Obviously, according to the content of the specification, many modifications and changes can be made. The specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the application, so that those skilled in the art can well understand and use the application. The application is limited by the claims and their entire scope and equivalents.

Claims

1. A method for early warning of failure of an electric drive system, characterized in that The fault early warning method process is as follows: Battery characteristic diagnosis, battery characteristic diagnosis is performed during the supply stage, the supply performance of the battery pack inside the electric drive system is detected in real time through battery characteristic diagnosis, battery characteristic diagnosis information is collected, and a characteristic diagnosis coefficient is obtained through calculation, whether the characteristic diagnosis of the energy storage body is abnormal is inferred according to the coefficient, yes, characteristic early warning is performed, no, the next step is performed; Running environment control characteristic diagnosis, after the battery characteristic diagnosis is qualified, the running energy supply environment of the battery inside the electric drive system and the influence of environmental control are analyzed synchronously, ring temperature influence information and ring speed influence information are collected, whether the running environment characteristic diagnosis of the electric drive system is abnormal is inferred according to the information, yes, parameter regulation is performed, no, the next step is performed; Tire energy supply characteristic diagnosis, after entering the supply stage, the electric drive system supplies energy to the tire, analyzes and diagnoses the running characteristics of the tire during the energy supply process, and marks the tire as a direct supply object, collects tire energy supply characteristic information, and obtains an energy supply characteristic diagnosis coefficient according to calculation, a curve is constructed according to the coefficient, a threshold value is set to construct a parameter boundary line, and the tire is divided into a tire high-efficiency section and a tire low-efficiency section through the parameter boundary line, whether the tire energy supply characteristics are qualified is inferred through corresponding type period analysis; Energy supply efficiency characteristic diagnosis, after the electric drive system completes tire energy supply and the characteristic diagnosis is qualified, energy supply efficiency characteristic analysis and diagnosis are performed, supply stall data and supply delay data are collected, and whether the energy supply efficiency characteristic diagnosis of the electric drive system is abnormal is inferred according to data analysis.

2. The method of claim 1, wherein, The battery characteristic diagnosis information includes the maximum interval time span increase span of the adjacent cycle charging and discharging, the charging speed floating deviation of each energy storage module in the energy storage body at different charging temperatures, and the maximum deviation value of the remaining amount of any amount of energy storage modules in the energy storage body at the same discharging speed during the discharging stage.

3. The method of claim 2, wherein, If the characteristic diagnosis coefficient exceeds the characteristic diagnosis coefficient threshold value, it is inferred that the characteristic diagnosis of the energy storage body is abnormal; If the characteristic diagnosis coefficient does not exceed the characteristic diagnosis coefficient threshold value, it is inferred that the characteristic diagnosis of the energy storage body is normal.

4. The method of claim 1, wherein, The ring temperature influence information and the ring speed influence information are respectively the peak value of the real-time charging temperature rise span and the cumulative sum of the capacity floating span of the energy storage body during the temperature rise stage, and the total number of speed deviation time points corresponding to the charging port power supply speed and the energy storage body power filling speed during the charging temperature rise stage accounts for the proportion; If the ring temperature influence information exceeds the span cumulative sum threshold value, or the ring speed influence information exceeds the time point number proportion threshold value, an environment control characteristic abnormal signal is generated; If the ring temperature influence information does not exceed the span cumulative sum threshold value, and the ring speed influence information does not exceed the time point number proportion threshold value, an environment control characteristic normal signal is generated.

5. The method of claim 1, wherein, The tire energy supply characteristic information includes the speed deviation value of the rubber tire rotation speed and the wheel shaft center rotation speed in the direct supply object, and the number of revolutions increase span of the wheel at the same position when the direct supply object appears speed deviation value; During the new energy electric vehicle driving period, the energy supply characteristic diagnosis coefficient of the direct supply object is counted and a coefficient curve is constructed according to each time point, a parameter boundary line is obtained according to the coefficient threshold value, and the coefficient curve is divided into a tire high-efficiency section and a tire low-efficiency section according to the parameter boundary line.

6. The method of claim 5, wherein, Collect high-float data and high-stable data, and the high-float data and the high-stable data are respectively the maximum value of the floating span of the corresponding curve of the electric vehicle starting period in the tire high-efficiency period, and the average value of the reciprocating floating span of the corresponding curve of any driving moment in the tire high-efficiency period; If the high-float data exceeds the peak value threshold of the floating span, or the high-stable data exceeds the average value threshold of the reciprocating span, the current tire high-efficiency period is determined as a high-efficiency unstable period; If the high-float data does not exceed the peak value threshold of the floating span, and the high-stable data does not exceed the average value threshold of the reciprocating span, the current tire high-efficiency period is determined as a high-efficiency stable period.

7. The method of claim 6, wherein the step of determining the fault condition comprises: Collect low-uniform float data and low-decrease float data, and the low-uniform float data and the low-decrease float data are respectively the floating frequency of the corresponding curve of the electric vehicle uniform driving period in the tire low-efficiency period and the increase frequency of the floating span of the corresponding curve of the electric vehicle deceleration driving period; If the low-uniform float data exceeds the floating frequency threshold, or the low-decrease float data exceeds the increase frequency threshold of the floating span, the current tire low-efficiency period is determined as a low-efficiency unstable period; if the low-uniform float data does not exceed the floating frequency threshold, and the low-decrease float data does not exceed the increase frequency threshold of the floating span, the current tire low-efficiency period is determined as a low-efficiency stable period.

8. The method of claim 7, wherein, If the cumulative length ratio of the high-efficiency stable period and the low-efficiency stable period exceeds the cumulative length ratio threshold, it is inferred that the current electric drive system tire energy supply is qualified; If the length ratio of the low-efficiency unstable period exceeds the low-efficiency length ratio threshold, it is inferred that the current electric drive system tire energy supply is inefficient; if the length ratio of the high-efficiency unstable period exceeds the high-efficiency length ratio threshold, it is inferred that the current electric drive system tire energy supply is abnormal.

9. The method of claim 1, wherein, The supply stall data and the supply delay data are respectively the vehicle speed floating value caused by the power supply amount decrease of the electric drive system supply stage when the electric vehicle drives without floating, and the supply delay span of the electric drive system supply stage when the driving speed of the electric vehicle floats; If the supply stall data exceeds the vehicle speed floating threshold, or the supply delay data exceeds the supply delay threshold, a power supply danger signal is generated; if the supply stall data does not exceed the vehicle speed floating threshold, and the supply delay data does not exceed the supply delay threshold, a power supply normal signal is generated.

10. An electric drive system failure early warning system characterized by, The electric drive system fault early warning method according to any one of claims 1-9.

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