CN113673026A - Method and system for calculating random electromagnetic vibration characteristics of hub motor - Google Patents

Method and system for calculating random electromagnetic vibration characteristics of hub motor Download PDF

Info

Publication number
CN113673026A
CN113673026A CN202110779575.8A CN202110779575A CN113673026A CN 113673026 A CN113673026 A CN 113673026A CN 202110779575 A CN202110779575 A CN 202110779575A CN 113673026 A CN113673026 A CN 113673026A
Authority
CN
China
Prior art keywords
random
hub motor
vibration
rotor
calculating
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202110779575.8A
Other languages
Chinese (zh)
Other versions
CN113673026B (en
Inventor
张海军
万少华
张明杰
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hubei University of Arts and Science
Original Assignee
Hubei University of Arts and Science
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hubei University of Arts and Science filed Critical Hubei University of Arts and Science
Priority to CN202110779575.8A priority Critical patent/CN113673026B/en
Publication of CN113673026A publication Critical patent/CN113673026A/en
Application granted granted Critical
Publication of CN113673026B publication Critical patent/CN113673026B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/10—Geometric CAD
    • G06F30/15—Vehicle, aircraft or watercraft design
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
    • 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
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Geometry (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Hardware Design (AREA)
  • General Engineering & Computer Science (AREA)
  • Evolutionary Computation (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Optimization (AREA)
  • Mathematical Analysis (AREA)
  • Computational Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Arrangement Or Mounting Of Propulsion Units For Vehicles (AREA)

Abstract

The invention discloses a method and a system for calculating the random electromagnetic vibration characteristic of a hub motor.

Description

Method and system for calculating random electromagnetic vibration characteristics of hub motor
Technical Field
The invention relates to a method and a system for calculating random electromagnetic vibration characteristics of a hub motor, and belongs to the field of new energy electric automobiles.
Background
The hub motor is used as a key part for driving the hub of the electric automobile, the performance of the hub motor directly determines the dynamic performance of the automobile, however, the hub motor is influenced by random vibration generated by road unevenness in the running process, so that the contradiction between the smoothness and the operation stability of the electric automobile is excited, and the riding comfort and the driving safety of the automobile are influenced.
One of the main factors causing the vibration of the in-wheel motor is the unbalanced radial electromagnetic force of the motor. Because the unbalanced radial electromagnetic force directly acts on the wheel without vibration reduction, the working environment of the motor can be deteriorated, the fatigue life of the motor can be reduced, the dynamic load of the tire can be increased, the ground gripping attachment capacity of the tire can be reduced, and the rollover risk of the automobile can be increased.
Aiming at the problem of random vibration of the hub motor, the prior art only aims at the problem that the excitation of the road surface can influence the vibration of the hub motor to carry out single research, and the research is analyzed from the outside of the motor, and the influence of the random vibration factor of the road surface on the electromagnetic change in the motor is not further considered, so that the influence of the random vibration factor of the road surface on the electromagnetic vibration characteristic of the hub motor cannot be truly reflected.
Disclosure of Invention
The invention provides a method and a system for calculating the random electromagnetic vibration characteristics of an in-wheel motor, which solve the problems disclosed in the background art.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
a method for calculating the random electromagnetic vibration characteristics of an in-wheel motor comprises the following steps:
according to the road surface unevenness, carrying out random dynamic analysis on the body and the wheels of the electric automobile to obtain random vibration factors influencing a hub motor;
carrying out dynamic eccentricity analysis on the stator and the rotor of the hub motor, and calculating the eccentricity of the stator and the rotor of the hub motor according to random vibration factors;
calculating the air gap flux density when the rotor of the hub motor is eccentric according to the eccentricity of the stator and the rotor of the hub motor;
calculating the radial electromagnetic force of the hub motor according to the air gap flux density;
and calculating the acceleration transfer function of the radial electromagnetic force reflecting the random electromagnetic vibration characteristic of the hub motor according to the radial electromagnetic force.
According to the road surface unevenness, the random dynamics analysis of the electric automobile body and the wheels is carried out, the random vibration factors influencing the hub motor are obtained, and the specific process is as follows:
according to the road surface unevenness, performing random dynamic analysis on the body and wheels of the electric automobile, and constructing a road surface power spectral density fitting function and an electric automobile vibration model;
and acquiring random vibration factors influencing the hub motor according to the road surface power spectral density fitting function and the electric automobile vibration model.
The road surface power spectral density fitting function is as follows:
Figure BDA0003155906440000021
where n is the spatial frequency and n is0For reference to spatial frequency, Gq(n0) Is a reference spatial frequency n0The road surface unevenness q coefficient, omega, is a frequency index, GqAnd (n) is the road surface power spectral density.
The electric automobile vibration model is as follows:
Figure BDA0003155906440000022
wherein m is1、m2、m0Respectively vehicle body mass, hub motor mass and tire mass, k1、k2、k0Respectively the automobile suspension stiffness, the hub motor stiffness and the tire spring stiffness, c1、c2、c0Respectively are the damping coefficient of the automobile suspension shock absorber, the damping coefficient of the hub motor and the damping coefficient of the tire, q is the road surface unevenness,
Figure BDA0003155906440000031
are respectively mnN is 1,2, 0.
The random vibration factors are:
Figure BDA0003155906440000032
wherein beta is a random vibration factor, lambda is a frequency ratio, q is road surface unevenness, and zeta is a damping ratio.
The air gap flux density is calculated as:
Br＝kN2λlIsin(ωt+θ)
wherein k is a proportionality coefficient, N is the number of turns of the stator winding, I is a peak current, and omegaeIs the angular frequency of rotation of the rotor, BrIs the air gap flux density, theta is the rotor angle,
Figure BDA0003155906440000033
being air-gap permeance, gamma0The length of a uniform air gap between the stator and the rotor when no eccentricity exists, alpha is the angle of the eccentric direction of the rotor, and e is the eccentricity of the stator and the rotor of the hub motor.
According to the air gap magnetic flux density, calculating the radial electromagnetic force of the hub motor, and the specific process is as follows:
and according to the air gap magnetic flux density, integrating the rotor angle to obtain the radial electromagnetic force of the hub motor.
The radial electromagnetic force calculation formula of the hub motor is as follows:
Figure BDA0003155906440000034
wherein, Fr,βIs the radial electromagnetic force of the hub motor, theta is the rotor angle, mu0Is magnetic permeability.
The radial electromagnetic force acceleration transfer function is:
Figure BDA0003155906440000035
wherein, H (s, beta), a (s, beta), Fr(s, beta) are respectively a radial electromagnetic force acceleration transfer function, an acceleration response and a radial electromagnetic force under the influence of a random vibration factor beta, and s is a Laplace variable.
An in-wheel motor random electromagnetic vibration characteristic calculation system, comprising:
a random vibration factor acquisition module: according to the road surface unevenness, carrying out random dynamic analysis on the body and the wheels of the electric automobile to obtain random vibration factors influencing a hub motor;
an eccentricity calculation module: carrying out dynamic eccentricity analysis on the stator and the rotor of the hub motor, and calculating the eccentricity of the stator and the rotor of the hub motor according to random vibration factors;
air gap flux density calculation module: calculating the air gap flux density when the rotor of the hub motor is eccentric according to the eccentricity of the stator and the rotor of the hub motor;
radial electromagnetic force calculation module: calculating the radial electromagnetic force of the hub motor according to the air gap flux density;
a transfer function calculation module: and calculating the acceleration transfer function of the radial electromagnetic force reflecting the random electromagnetic vibration characteristic of the hub motor according to the radial electromagnetic force.
The invention achieves the following beneficial effects: the invention integrates random vibration mechanics and electromagnetics, calculates the radial electromagnetic force vibration acceleration transfer function of the hub motor under random vibration factors, and can analyze the electromagnetic characteristics of the hub motor under random vibration based on the transfer function, thereby more comprehensively reflecting the influence of the road random vibration factors on the electromagnetic vibration of the hub motor, namely the random electromagnetic vibration characteristics of the hub motor.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic view of the coupled vibration of the hub motor;
fig. 3 is a schematic diagram of the eccentricity of the rotor of the in-wheel motor.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
As shown in fig. 1, a method for calculating the random electromagnetic vibration characteristics of an in-wheel motor includes the following steps:
step 1, performing random dynamics analysis on an electric automobile body and wheels according to road unevenness to obtain random vibration factors affecting a hub motor;
step 2, carrying out dynamic eccentricity analysis on the stator and the rotor of the hub motor, and calculating the eccentricity of the stator and the rotor of the hub motor according to random vibration factors;
step 3, calculating the air gap flux density when the rotor of the hub motor is eccentric according to the eccentricity of the stator and the rotor of the hub motor;
step 4, calculating the radial electromagnetic force of the hub motor according to the air gap flux density;
and 5, calculating a radial electromagnetic force acceleration transfer function reflecting the random electromagnetic vibration characteristic of the hub motor according to the radial electromagnetic force.
The method integrates random vibration mechanics and electromagnetic mechanics, calculates the vibration acceleration transfer function of the radial electromagnetic force of the hub motor under the random vibration factors, and can analyze the electromagnetic characteristics of the hub motor under the random vibration based on the transfer function, thereby more comprehensively reflecting the influence of the road surface random vibration factors on the electromagnetic vibration of the hub motor, namely the random electromagnetic vibration characteristics of the hub motor.
The road surface unevenness is determined according to the actual walking road surface of the electric automobile, the random dynamic analysis of the electric automobile body and wheels is firstly carried out according to the road surface unevenness, a road surface power spectrum density fitting function and an electric automobile vibration model are constructed, and then the random vibration factors influencing the hub motor are obtained according to the road surface power spectrum density fitting function and the electric automobile vibration model.
The road surface power spectral density fitting function is as follows:
Figure BDA0003155906440000051
where n is the spatial frequency and n is0For reference to spatial frequency, Gq(n0) Is a reference spatial frequency n0The road surface unevenness q coefficient, omega, is a frequency index, GqAnd (n) is the road surface power spectral density.
As a complex nonlinear system, the vibration analysis of the electric vehicle is a coupled system with multiple degrees of freedom, and an 1/4 vehicle vertical vibration model shown in FIG. 2 is established on the assumption that the body mass of the electric vehicle is evenly distributed to all wheels.
And (3) deriving by taking the balance position of each mass block as a coordinate origin through a Newton second law to obtain a dynamic equation, namely the vibration model of the electric automobile is as follows:
Figure BDA0003155906440000061
wherein m is1、m2、m0Respectively vehicle body mass, hub motor mass and tire mass, k1、k2、k0Respectively the automobile suspension stiffness, the hub motor stiffness and the tire spring stiffness, c1、c2、c0Respectively are the damping coefficient of the automobile suspension shock absorber, the damping coefficient of the hub motor and the damping coefficient of the tire, q is the road surface unevenness,
Figure BDA0003155906440000062
are respectively mnN is 1,2, 0.
In the operation process of the hub motor, uneven road excitation and vehicle body load change can act on the hub motor and finally are converted into a random vibration factor beta of the hub motor, so that the random vibration factor influencing the hub motor is extracted through a road power spectral density fitting function and a two-degree-of-freedom vibration model, and the specific formula is as follows:
Figure BDA0003155906440000063
the amplitude-frequency characteristics of beta to q are as follows:
Figure BDA0003155906440000064
wherein beta is a random vibration factor, lambda is a frequency ratio, q is road surface unevenness, and zeta is a damping ratio.
Dynamic eccentricity analysis of a stator and a rotor of the hub motor: in the operation process of the hub motor, vertical electromagnetic forces can be mutually counteracted due to the fact that air gaps are uniformly distributed on the sections of the stator and the rotor, but in practical situations, as shown in fig. 3, due to the fact that eccentricity between the stator and the rotor is difficult to avoid, unbalanced distribution of the air gaps and magnetic fields is caused, and when only basic magnetic fields generated by permanent magnets and d-axis and q-axis currents are considered, a certain functional relation is presented between the eccentricity and random vibration factors.
Therefore, according to the random vibration factor, the eccentricity of the stator and the rotor of the hub motor can be calculated as follows:
e＝f(β)
wherein e is the eccentricity of the stator and the rotor of the hub motor, and f is a relation function between e and beta.
Based on a wheel hub motor rotor coordinate system, the length of an air gap between a stator and a rotor of the motor is obtained, and the air gap magnetic conductance is as follows:
Figure BDA0003155906440000071
wherein, γ0The length of a uniform air gap between the fixed rotors without eccentricity, and alpha is the angle of the eccentric direction of the rotors; omegaeIs the rotor rotational angular frequency;
the air gap flux density is then found to be:
Br＝kN2λlIsin(ωet+θ)
wherein k is a proportionality coefficient, N is the number of turns of the stator winding, I is a peak current, and BrFor air gap flux density, θ is the rotor angle.
Because radial electromagnetic force is the main source of radial electromagnetic vibration, according to air gap flux density, carry out the integral to the rotor angle, can obtain the radial electromagnetic force of in-wheel motor, specifically as follows:
Figure BDA0003155906440000072
wherein, Fr,βRadial electromagnetic force, mu, for hub motors0Is magnetic permeability.
The vibration of the hub motor can be expressed as a mechanical model on a damping spring system, and a vibration equation is obtained by Newton's second law
Figure BDA0003155906440000081
According to the Laplace transform, the displacement response, the speed response and the acceleration response of the system are obtained, and therefore the radial electromagnetic force acceleration transfer function reflecting the random electromagnetic vibration characteristic of the hub motor is obtained, and the method specifically comprises the following steps:
Figure BDA0003155906440000082
wherein, H (s, beta), a (s, beta), Fr(s, beta) are respectively a radial electromagnetic force acceleration transfer function, an acceleration response and a radial electromagnetic force under the influence of a random vibration factor beta, and s is a Laplace variable
The invention provides a random electromagnetic vibration analysis method of an electric automobile hub motor, integrates random vibration mechanics and electromagnetic mechanics, more comprehensively and deeply analyzes and researches the influence of the electromagnetic characteristics of the hub motor, more truly reflects the electromagnetic characteristics of the hub motor under random vibration, and lays a certain foundation for solving the vibration problem of the hub motor and increasing the driving smoothness and riding comfort of an automobile in the future.
An in-wheel motor random electromagnetic vibration characteristic calculation system, comprising:
a random vibration factor acquisition module: according to the road surface unevenness, carrying out random dynamic analysis on the body and the wheels of the electric automobile to obtain random vibration factors influencing a hub motor;
an eccentricity calculation module: carrying out dynamic eccentricity analysis on the stator and the rotor of the hub motor, and calculating the eccentricity of the stator and the rotor of the hub motor according to random vibration factors;
air gap flux density calculation module: calculating the air gap flux density when the rotor of the hub motor is eccentric according to the eccentricity of the stator and the rotor of the hub motor;
radial electromagnetic force calculation module: calculating the radial electromagnetic force of the hub motor according to the air gap flux density;
a transfer function calculation module: and calculating the acceleration transfer function of the radial electromagnetic force reflecting the random electromagnetic vibration characteristic of the hub motor according to the radial electromagnetic force.
A computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a computing device, cause the computing device to perform a hub motor random electromagnetic vibration characteristic calculation method.
A computing device comprising one or more processors, one or more memories, and one or more programs stored in the one or more memories and configured to be executed by the one or more processors, the one or more programs comprising instructions for performing a method for calculating a random electromagnetic vibration characteristic of an in-wheel motor.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The present invention is not limited to the above embodiments, and any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention are included in the scope of the claims of the present invention which are filed as the application.

Claims (10)

1. A method for calculating the random electromagnetic vibration characteristics of an in-wheel motor is characterized by comprising the following steps:
according to the road surface unevenness, carrying out random dynamic analysis on the body and the wheels of the electric automobile to obtain random vibration factors influencing a hub motor;
carrying out dynamic eccentricity analysis on the stator and the rotor of the hub motor, and calculating the eccentricity of the stator and the rotor of the hub motor according to random vibration factors;
calculating the air gap flux density when the rotor of the hub motor is eccentric according to the eccentricity of the stator and the rotor of the hub motor;
calculating the radial electromagnetic force of the hub motor according to the air gap flux density;
and calculating the acceleration transfer function of the radial electromagnetic force reflecting the random electromagnetic vibration characteristic of the hub motor according to the radial electromagnetic force.
2. The method for calculating the random electromagnetic vibration characteristics of the in-wheel motor according to claim 1, wherein the random dynamic analysis of the body and the wheels of the electric vehicle is performed according to the road unevenness, and the random vibration factors affecting the in-wheel motor are obtained by the following specific processes:
according to the road surface unevenness, performing random dynamic analysis on the body and wheels of the electric automobile, and constructing a road surface power spectral density fitting function and an electric automobile vibration model;
and acquiring random vibration factors influencing the hub motor according to the road surface power spectral density fitting function and the electric automobile vibration model.
3. The method for calculating the random electromagnetic vibration characteristics of the in-wheel motor according to claim 2, wherein the road surface power spectral density fitting function is as follows:
Figure FDA0003155906430000011
where n is the spatial frequency and n is0For reference to spatial frequency, Gq(n0) Is a reference spatial frequency n0The road surface unevenness q coefficient, omega, is a frequency index, GqAnd (n) is the road surface power spectral density.
4. The method for calculating the random electromagnetic vibration characteristic of the in-wheel motor according to claim 2, wherein the vibration model of the electric vehicle is as follows:
Figure FDA0003155906430000021
wherein m is1、m2、m0Respectively vehicle body mass, hub motor mass and tire mass, k1、k2、k0Respectively the automobile suspension stiffness, the hub motor stiffness and the tire spring stiffness, c1、c2、c0Respectively are damping coefficient of automobile suspension shock absorber, damping coefficient of hub motor and damping coefficient of tyre, q is road surface unevenness, xn、
Figure FDA0003155906430000022
Are respectively mnN is 1,2, 0.
5. A method for calculating the random electromagnetic vibration characteristics of an in-wheel motor according to claim 1 or 2, wherein the random vibration factors are:
Figure FDA0003155906430000023
wherein beta is a random vibration factor, lambda is a frequency ratio, q is road surface unevenness, and zeta is a damping ratio.
6. The in-wheel motor random electromagnetic vibration characteristic calculation method according to claim 1, wherein the air gap flux density calculation formula is:
Br＝kN2λlIsin(ωet+θ)
wherein k is a proportionality coefficient, N is the number of turns of the stator winding, I is a peak current, and omegaeIs the angular frequency of rotation of the rotor, BrIs the air gap flux density, theta is the rotor angle,
Figure FDA0003155906430000024
being air-gap permeance, gamma0The length of a uniform air gap between the stator and the rotor when no eccentricity exists, alpha is the angle of the eccentric direction of the rotor, and e is the eccentricity of the stator and the rotor of the hub motor.
7. The method for calculating the random electromagnetic vibration characteristic of the in-wheel motor according to the claim 1, wherein the radial electromagnetic force of the in-wheel motor is calculated according to the air gap flux density by the following specific process:
and according to the air gap magnetic flux density, integrating the rotor angle to obtain the radial electromagnetic force of the hub motor.
8. The in-wheel motor random electromagnetic vibration characteristic calculation method according to claim 7, wherein the radial electromagnetic force calculation formula of the in-wheel motor is as follows:
Figure FDA0003155906430000031
wherein, Fr,βIs the radial electromagnetic force of the hub motor, theta is the rotor angle, mu0Is magnetic permeability.
9. The in-wheel motor random electromagnetic vibration characteristic calculation method according to claim 1, wherein the radial electromagnetic force acceleration transfer function is:
Figure FDA0003155906430000032
wherein, H (s, beta), a (s, beta), Fr(s, beta) are respectively a radial electromagnetic force acceleration transfer function, an acceleration response and a radial electromagnetic force under the influence of a random vibration factor beta, and s is a Laplace variable.
10. An in-wheel motor random electromagnetic vibration characteristic calculation system, comprising:
a random vibration factor acquisition module: according to the road surface unevenness, carrying out random dynamic analysis on the body and the wheels of the electric automobile to obtain random vibration factors influencing a hub motor;
an eccentricity calculation module: carrying out dynamic eccentricity analysis on the stator and the rotor of the hub motor, and calculating the eccentricity of the stator and the rotor of the hub motor according to random vibration factors;
air gap flux density calculation module: calculating the air gap flux density when the rotor of the hub motor is eccentric according to the eccentricity of the stator and the rotor of the hub motor;
radial electromagnetic force calculation module: calculating the radial electromagnetic force of the hub motor according to the air gap flux density;
a transfer function calculation module: and calculating the acceleration transfer function of the radial electromagnetic force reflecting the random electromagnetic vibration characteristic of the hub motor according to the radial electromagnetic force.
CN202110779575.8A 2021-07-09 2021-07-09 Method and system for calculating random electromagnetic vibration characteristics of hub motor Active CN113673026B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110779575.8A CN113673026B (en) 2021-07-09 2021-07-09 Method and system for calculating random electromagnetic vibration characteristics of hub motor

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110779575.8A CN113673026B (en) 2021-07-09 2021-07-09 Method and system for calculating random electromagnetic vibration characteristics of hub motor

Publications (2)

Publication Number Publication Date
CN113673026A true CN113673026A (en) 2021-11-19
CN113673026B CN113673026B (en) 2023-08-04

Family

ID=78538768

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110779575.8A Active CN113673026B (en) 2021-07-09 2021-07-09 Method and system for calculating random electromagnetic vibration characteristics of hub motor

Country Status (1)

Country Link
CN (1) CN113673026B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114061880A (en) * 2021-11-23 2022-02-18 哈尔滨理工大学 Electromagnetic coupling vibration test system and control strategy for high-speed rotation of direct-drive hub motor

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109522670A (en) * 2018-11-29 2019-03-26 山东理工大学 A kind of wheel hub driving vehicle multi-source excitation Coupling Dynamics Analysis method
US20190173414A1 (en) * 2018-01-29 2019-06-06 Yangzhou University Prediction Method for Reliability Degree of Running Temperature Rise of a Large and Medium-sized Motor
CN111122080A (en) * 2018-10-31 2020-05-08 株洲中车时代电气股份有限公司 Traction motor vibration test method and system

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190173414A1 (en) * 2018-01-29 2019-06-06 Yangzhou University Prediction Method for Reliability Degree of Running Temperature Rise of a Large and Medium-sized Motor
CN111122080A (en) * 2018-10-31 2020-05-08 株洲中车时代电气股份有限公司 Traction motor vibration test method and system
CN109522670A (en) * 2018-11-29 2019-03-26 山东理工大学 A kind of wheel hub driving vehicle multi-source excitation Coupling Dynamics Analysis method

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
易科虹;陈晓育;华春蓉;董大伟;: "参数不确定性车辆的复合随机振动分析", 机械科学与技术, no. 06 *
李丽莉，过永德: "汽车振动系统的简化及其响应模拟", 华北工学院学报, no. 02 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114061880A (en) * 2021-11-23 2022-02-18 哈尔滨理工大学 Electromagnetic coupling vibration test system and control strategy for high-speed rotation of direct-drive hub motor
CN114061880B (en) * 2021-11-23 2024-01-30 哈尔滨理工大学 Electromagnetic coupling vibration testing system and control strategy for direct-drive type hub motor during high-speed rotation

Also Published As

Publication number Publication date
CN113673026B (en) 2023-08-04

Similar Documents

Publication Publication Date Title
Tan et al. The influence of the magnetic force generated by the in-wheel motor on the vertical and lateral coupling dynamics of electric vehicles
Qin et al. Vibration mitigation for in-wheel switched reluctance motor driven electric vehicle with dynamic vibration absorbing structures
Luo et al. Study on the dynamics of the in-wheel motor system
Wang et al. Electric vehicles with in-wheel switched reluctance motors: Coupling effects between road excitation and the unbalanced radial force
CN110949144B (en) Control method and system for output torque of electric automobile
Ma et al. A novel black and white box method for diagnosis and reduction of abnormal noise of hub permanent-magnet synchronous motors for electric vehicles
Yu et al. Influence of rotor-bearing coupling vibration on dynamic behavior of electric vehicle driven by in-wheel motor
CN107403040B (en) Vibration reduction design method for wheel hub motor driven vehicle based on vibration energy transmission
Qin et al. Study of longitudinal–vertical dynamics for in-wheel motor-driven electric vehicles
CN105539202A (en) Multi-shaft mine car torque distribution method and device
CN112054725B (en) System and method for maintaining torque in an electric vehicle
CN113673026B (en) Method and system for calculating random electromagnetic vibration characteristics of hub motor
Zuo et al. Analysis and suppression of longitudinal vibration of electric wheel system considering rotor position error
Li et al. Integrated design of active suspension parameters for solving negative vibration effects of switched reluctance-in-wheel motor electrical vehicles based on multi-objective particle swarm optimization
KR101956482B1 (en) Method and device for distributing power of hybrid vehicle with electric supercharger
Li et al. Analysis on electromechanical coupling vibration characteristics of in-wheel motor in electric vehicles considering air gap eccentricity
Li et al. Optimal design and dynamic control of the HMDV inertial suspension based on the ground-hook positive real network
Li et al. Influence of tire dynamics on slip ratio estimation of independent driving wheel system
Oubelaid et al. Robust controllers design and performance investigation of a vector controlled electric vehicle
CN106394157A (en) Electromagnetic suspension vibration isolation and energy feedback coordinating control method
Shi et al. Simulation and verification analysis of the ride comfort of an in-wheel motor-driven electric vehicle based on a combination of ADAMS and MATLAB
Chaturvedi et al. Regulation of electric vehicle speed oscillations due to uneven drive surfaces using ISMDTC
Côté et al. Design and Optimization of a high torque in-wheel surface-mounted PM synchronous motor using concentrated winding
Fujimoto et al. Pitching control method based on quick torque response for electric vehicle
Ringdorfer et al. A robust wheel slip controller for a hybrid braking system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant