CN110429893A - A kind of electric machine controller carrier frequency dynamic optimization method and electric machine controller - Google Patents
A kind of electric machine controller carrier frequency dynamic optimization method and electric machine controller Download PDFInfo
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- CN110429893A CN110429893A CN201910807336.1A CN201910807336A CN110429893A CN 110429893 A CN110429893 A CN 110429893A CN 201910807336 A CN201910807336 A CN 201910807336A CN 110429893 A CN110429893 A CN 110429893A
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- electric machine
- carrier frequency
- machine controller
- dynamic optimization
- frequency dynamic
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
- H02P23/00—Arrangements or methods for the control of AC motors characterised by a control method other than vector control
- H02P23/28—Controlling the motor by varying the switching frequency of switches connected to a DC supply and the motor phases
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- Control Of Ac Motors In General (AREA)
Abstract
The present invention relates to a kind of electric machine controller carrier frequency dynamic optimization methods, method includes the following steps: step S1: it is related with motor speed, torque and electric machine controller carrier frequency to establish objective function, constraint condition electric machine controller carrier frequency dynamic optimization model related with electric machine controller carrier frequency and sample frequency；Step S2: electric machine controller carrier frequency dynamic optimization model is solved using fuzzy logic method and obtains electric machine controller dynamic optimization carrier frequency.Compared with prior art, the loss that carrier frequency reduces electric machine controller can dynamically be changed in the case where guaranteeing harmonic distortion rate.
Description
Technical field
The present invention relates to power electronics and power drives fields, more particularly, to a kind of electric machine controller carrier frequency dynamic optimization
Method and electric machine controller.
Background technique
Due to Development of EV start-up time morning, they grind electric machine controller for Japan and American-European developed country
Study carefully and spent on developing more energy and times.Many automobile electronics business mens, such as German Continent Group, Bosch group
Company has also started electric machine controller research and development.Partial automobile components or luxuriant next, the Germany FEV of automotive development quotient start technology to have
Mostly etc., the status in electric car field is also very important for limit company, inner card.Since the developed countries such as America and Europe develop electronic vapour
Vehicle start-up time is early, causes them to have the electric vehicle development experience of very abundant, and their control strategy has very
High systematicness is also very preeminent in the control from view of profit of controller.And their automaker and some auto parts
Manufacturer, even some electronic device providers are proposed automobile open systems architecture together, the exploitation environment after being and
The use of electronic control unit provides simpler and more direct mode, and the research and development of controller is allowed to more tend to markization.
In recent years for developed country, the manufacture and research of Japanese electric car are all made of permanent magnet synchronous motor control
Device, and most of electric vehicle development quotient of China is also using Permanent Magnet Synchronous Motor Controller and to use matched control
The power of device, electric machine controller control can achieve 130 kilowatts or so, transport range with very big invariable power, revolving speed also can
Reach 4.7 times of rated value.And for Japan, American-European control technology and control strategy are also very mature, but he
It is most of using asynchronous motor control device as direct driving force source, more famous is exactly the Tesla (CS) Koncern, Podebradska 186, Praha 9, Czechoslovakia in the U.S., he
Electric vehicle be all made of asynchronous motor control device, and its controller performance is also very outstanding.
Include inverter in electric machine controller, includes IGBT (insulated gate bipolar transistor), the function of IGBT in inverter
Rate loss is related with carrier frequency, and increases with the raising of carrier frequency, power loss, first declines efficiency in this way, second
Be power module fever increase, to operation be it is unfavorable, the operating voltage of certain inverter is higher, and power loss also increases.It carries
Wave frequency rate is bigger, and the loss of inverter is bigger, and output power is smaller.If environment temperature is high, two inversion pipes above and below inverter bridge
Dead zone during alternate conduction will become smaller, and can lead to bridgc arm short when serious and damage inverter.Carrier frequency can also shadow
It rings and exports total harmonic distortion amount, influence noise of motor.
Summary of the invention
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide a kind of electric machine controllers to carry
Frequency dynamic optimization method and electric machine controller.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of electric machine controller carrier frequency dynamic optimization method, method includes the following steps:
Step S1: it is related with motor speed, torque and electric machine controller carrier frequency to establish objective function, constraint condition and motor
Controller carrier frequency and the related electric machine controller carrier frequency dynamic optimization model of sample frequency；
Step S2: it is dynamic that electric machine controller is obtained using fuzzy logic method solution electric machine controller carrier frequency dynamic optimization model
State optimizes carrier frequency.
Solve the step S1 objective function the following steps are included:
Step S11: system transfer efficiency is obtained according to the parameter of electric machine and inverter losses；
Step S12: it is obtained and motor speed, torque and electric machine controller carrier frequency according to torque formula and system transfer efficiency
Related objective function.
The system transfer efficiency are as follows:
η=PMotor output/(PMotor output+PThe loss of electric machine+PIGBT)
Wherein, η is system transfer efficiency, PIGBTFor inverter losses, PThe loss of electric machineIt is the motor control for including iron loss and copper loss
Device loss.
The PIGBTAre as follows:
PIGBT=kfC
Wherein, k is constant, fCFor carrier frequency.
The objective function are as follows:
η(fC)=(Tn)/(Tn+9550 (PIGBT+PThe loss of electric machine))
Wherein, T is Motor torque, and n is motor speed.
The constraint condition are as follows:
fS=3KfC
fmin≤fC≤fmax
Wherein, K is integer, fCFor carrier frequency, fSFor sample frequency, fminAnd fmaxFor electric machine controller maximal work frequency
Rate.
The fuzzy logic method is Mamdani fuzzy reasoning method.
The fuzzy logic method is solved using gravity model appoach.
A kind of electric machine controller carries out carrier frequency dynamic using the electric machine controller carrier frequency dynamic optimization method and controls.
Compared with prior art, the invention has the following advantages that
(1) electric machine controller carrier frequency dynamic optimization model can dynamically change in the case where guaranteeing harmonic distortion rate and carry
Wave frequency rate reduces the loss of electric machine controller.
(2) it, that is, by the variation of detection electric car revolving speed and torque, can be obtained according to the operating condition of electric car
Real-time dynamic carrier frequency.
(3) by fuzzy logic method calculate dynamic carrier frequency, by the qualitative understanding of industrial process, be easier to establish
Linguistic control law, and strong robustness.
(4) fuzzy logic method is solved using gravity model appoach, and calculating speed is fast, can find optimal location quickly.
Detailed description of the invention
Fig. 1 is flow chart of the invention.
Specific embodiment
The present invention is described in detail with specific embodiment below in conjunction with the accompanying drawings.The present embodiment is with technical solution of the present invention
Premised on implemented, the detailed implementation method and specific operation process are given, but protection scope of the present invention is not limited to
Following embodiments.
Embodiment
The present embodiment will establish electric machine controller carrier frequency dynamic optimization model, in the feelings that THD (harmonic distortion) is met the requirements
Under condition, model is optimized by theoretical calculation so that system with output power of motor, carrier frequency variation efficiency most
It is excellent, to obtain dynamic carrier optimization frequency.Using dynamic carrier frequency technology, especially in the slow-speed of revolution, carrier frequency is required less
When high, the loss of electric machine controller is can be effectively reduced in adjustment carrier frequency, improves the efficiency of electric machine controller, according to preliminary estimation often
100 kilometers can be improved 1.5 kilometers or so of course continuation mileage.
(1) electric machine controller carrier frequency dynamic optimization model
The efficiency Model of system is optimized, and an electric machine controller carrier frequency dynamic optimization model can be constructed.
1.1 system effectiveness model foundations
Regard the parameter of electric machine and inverter as a total system to consider.Obtain the energy conversion efficiency of system:
η=PMotor output/(PMotor output+PThe loss of electric machine+PIGBT) (1-1)
In formula: where η is system transfer efficiency, PIGBTFor inverter losses, PThe loss of electric machineIt is the electricity for including iron loss and copper loss
Machine loss.
PIGBTIt is related with carrier frequency:
PIGBT=kfC
Wherein, fCFor carrier frequency.
Substantially η is about carrier frequency fCFunction.
Again by torque formula:
T=9550P/n (1-2)
Wherein T is Motor torque, and n is motor speed, and P is output power of motor.
Objective function related with motor speed, torque and carrier frequency can be obtained by bringing formula (1-2) into (1-1):
η(fC)=(Tn)/(Tn+9550 (PIGBT+PThe loss of electric machine)) (1-3)
1.2 constraint condition
1) carrier frequency not only will affect the efficiency of output, also will affect rate of total harmonics.Therefore, optimization object function
While we must optimize rate of total harmonics.Next to bipolarity SVPWM (space vector pulse width modulation) into
Row modeling:
THD constraint condition is set, i.e.,
fS=3KfC (1-4)
fSFor fC3 integral multiple time-harmonic wave ingredient it is minimum.
2) switching device also has bound requirement to carrier frequency, i.e.,
fmin≤fC≤fmax (1-5)
Wherein, K is integer, fSFor sample frequency, fminAnd fmaxFor electric machine controller working frequency limit.
1.3 optimization algorithm
To the analysis of electric machine controller carrier frequency dynamic optimization model it can be concluded that, rate of total harmonics and carrier frequency fCIt presents
Negative correlativing relation, i.e. carrier frequency are bigger, and harmonic content is smaller instead.
Defined variable: fuzzy logic controller includes two input variables and an output variable.Input turns including motor
Square and revolving speed export as carrier frequency.Compositional rule of inference algorithm uses Mamdani reasoning, and three preconditions take the minimum factor,
Conclusion part takes the maximization factor, and ambiguity solution uses gravity model appoach (COA).The domain of input and output is T={ LE ME GE }；N=
{LE ME GE}；FSW={ PS LE ME GE }.The carrier frequency member function of output is just small (PS, Positive small),
Small (LE, Little), in (ME, Middle), it is big (GE, Great).
Table 1 is fuzzy reasoning table:
1 control rule table of table
Existing technology substantially uses vector controlled and Direct Torque Control, and essence is the modulating wave for changing PWM.And
The present embodiment is the operating condition for electric car, using continuous modulation, changes the carrier wave of PWM, the starting point of technology is drop
Low electric machine controller loss, harmonic wave is also met the requirements under certain constraint condition.
The present embodiment makes carrier frequency Filled function according to electric car operating condition situation, using fuzzy control, i.e., using company
Continuous modulation, dynamic change carrier frequency and reduce electric machine controller loss.In big torque, the slow-speed of revolution declines low carrier frequency, can be with
Reduce electric machine controller loss.
The present embodiment can be applied on ev industry, can also apply in the motion control field that load changes greatly
It closes.
Claims (9)
1. a kind of electric machine controller carrier frequency dynamic optimization method, which is characterized in that method includes the following steps:
Step S1: it is related with motor speed, torque and electric machine controller carrier frequency to establish objective function, constraint condition and motor control
Device carrier frequency and the related electric machine controller carrier frequency dynamic optimization model of sample frequency；
Step S2: it is excellent that electric machine controller dynamic is obtained using fuzzy logic method solution electric machine controller carrier frequency dynamic optimization model
Change carrier frequency.
2. a kind of electric machine controller carrier frequency dynamic optimization method according to claim 1, which is characterized in that described in solving
Step S1 objective function the following steps are included:
Step S11: system transfer efficiency is obtained according to the parameter of electric machine and inverter losses；
Step S12: it is obtained according to torque formula and system transfer efficiency related with motor speed, torque and electric machine controller carrier frequency
Objective function.
3. a kind of electric machine controller carrier frequency dynamic optimization method according to claim 2, which is characterized in that the system
Transfer efficiency are as follows:
η=PMotor output/(PMotor output+PThe loss of electric machine+PIGBT)
Wherein, η is system transfer efficiency, PIGBTFor inverter losses, PThe loss of electric machineIt is the electric machine controller damage for including iron loss and copper loss
Consumption.
4. a kind of electric machine controller carrier frequency dynamic optimization method according to claim 2, which is characterized in that the PIGBT
Are as follows:
PIGBT=kfC
Wherein, k is constant, fCFor carrier frequency.
5. a kind of electric machine controller carrier frequency dynamic optimization method according to claim 2, which is characterized in that the target
Function are as follows:
η(fC)=(Tn)/(Tn+9550 (PIGBT+PThe loss of electric machine))
Wherein, T is Motor torque, and n is motor speed.
6. a kind of electric machine controller carrier frequency dynamic optimization method according to claim 1, which is characterized in that the constraint
Condition are as follows:
fS=3KfC
fmin≤fC≤fmax
Wherein, K is integer, fCFor carrier frequency, fSFor sample frequency, fminAnd fmaxFor electric machine controller working frequency limit.
7. a kind of electric machine controller carrier frequency dynamic optimization method according to claim 1, which is characterized in that described is fuzzy
Logical method is Mamdani fuzzy reasoning method.
8. a kind of electric machine controller carrier frequency dynamic optimization method according to claim 1, which is characterized in that described is fuzzy
Logical method is solved using gravity model appoach.
9. a kind of electric machine controller, which is characterized in that excellent using any electric machine controller carrier frequency dynamic of claim 1-8
Change method carries out carrier frequency dynamic and controls.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112152523A (en) * | 2020-09-21 | 2020-12-29 | 武汉大学 | NN/GA-based energy-saving speed regulation method for direct current motor |
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| CN106208785A (en) * | 2016-07-25 | 2016-12-07 | 武汉大学 | A kind of method for designing of inverter based on optimum carrier frequency |
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| JP2018148772A (en) * | 2017-03-09 | 2018-09-20 | アイシン精機株式会社 | Pump control device |
| CN109783916A (en) * | 2019-01-02 | 2019-05-21 | 大连理工大学 | A kind of air compressor group Optimized Operation decision-making technique based on emulation technology |
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| CN102692289A (en) * | 2012-06-25 | 2012-09-26 | 安徽安凯汽车股份有限公司 | Test system and method for measuring efficiency of electric driving system of novel-energy automobile |
| CN106208785A (en) * | 2016-07-25 | 2016-12-07 | 武汉大学 | A kind of method for designing of inverter based on optimum carrier frequency |
| JP2018148772A (en) * | 2017-03-09 | 2018-09-20 | アイシン精機株式会社 | Pump control device |
| CN106992661A (en) * | 2017-04-17 | 2017-07-28 | 广西大学 | The over-sampling real-time signal processing method controlled for PWM count word |
| CN109783916A (en) * | 2019-01-02 | 2019-05-21 | 大连理工大学 | A kind of air compressor group Optimized Operation decision-making technique based on emulation technology |
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