CN105882648B - A kind of hybrid power system energy management method based on fuzzy logic algorithm - Google Patents
A kind of hybrid power system energy management method based on fuzzy logic algorithm Download PDFInfo
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- CN105882648B CN105882648B CN201610300469.6A CN201610300469A CN105882648B CN 105882648 B CN105882648 B CN 105882648B CN 201610300469 A CN201610300469 A CN 201610300469A CN 105882648 B CN105882648 B CN 105882648B
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W20/00—Control systems specially adapted for hybrid vehicles
- B60W20/10—Controlling the power contribution of each of the prime movers to meet required power demand
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
- B60W10/06—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of combustion engines
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W10/00—Conjoint control of vehicle sub-units of different type or different function
- B60W10/04—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units
- B60W10/08—Conjoint control of vehicle sub-units of different type or different function including control of propulsion units including control of electric propulsion units, e.g. motors or generators
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2510/00—Input parameters relating to a particular sub-units
- B60W2510/24—Energy storage means
- B60W2510/242—Energy storage means for electrical energy
- B60W2510/244—Charge state
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2530/00—Input parameters relating to vehicle conditions or values, not covered by groups B60W2510/00 or B60W2520/00
- B60W2530/209—Fuel quantity remaining in tank
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2710/00—Output or target parameters relating to a particular sub-units
- B60W2710/06—Combustion engines, Gas turbines
- B60W2710/0677—Engine power
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2710/00—Output or target parameters relating to a particular sub-units
- B60W2710/08—Electric propulsion units
- B60W2710/086—Power
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/62—Hybrid vehicles
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- Chemical & Material Sciences (AREA)
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- Mechanical Engineering (AREA)
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- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
It is automatic to calculate vehicle power demand and power distribution combination in real time the invention discloses a kind of hybrid power system energy management method based on fuzzy logic algorithm, the fuel economy of vehicle is improved on the premise of ensureing dynamic property and meeting the needs of different users.Its technical scheme is：System self-test；Entire car controller sends calling-on signal to energy source controller, drive motor controller, obtains signal data；Judge whether signal data is complete；Entire car controller calculates vehicle demand power, vehicle dynamical system accessory power, each energy source power output is calculated in real time by fuzzy logic algorithm in real time according to signal data；Amendment is adjusted to the energy source power output being calculated in real time using fuzzy logic algorithm, to show that power distribution combines；Entire car controller is based on power distribution combination and sends power output allocation result to each energy source controller by CAN, completes real-time adjustment of the entire car controller to each energy source power output of dynamical system.
Description
Technical field
The present invention relates to hybrid vehicle control technology field, more particularly to the mixing realized based on fuzzy logic algorithm
Dynamical system energy management method.
Background technology
Stroke-increasing electric automobile is a kind of special mixed power electric car, it is intended to solves pure electric automobile course continuation mileage
The problem of short, on the basis of pure electric automobile, increase by 1 distance increasing unit to increase the course continuation mileage of electric automobile.Electrokinetic cell
As its main energy sources, range extender system is then its stand-by power source, when electrokinetic cell electric energy reduces to a certain extent, increases journey
Device is started working, and is power battery charging or direct drive vehicle, is increased automobile course continuation mileage.Dual-energy source system is in vehicle energy
Under the coordination control of management system, cooperated with miscellaneous part, a variety of optimum organizations can be carried out, form different dynamical systems
System mode of operation, to adapt to different driving cycles.
The target of energy management strategies is typically the multi-target non-linear with multiple input variables and multiple constraintss
Optimization problem, its control strategy have a significant impact to the power performance and the economy performance of vehicle.Generally reach the car of design
During operating range, vehicle-mounted energy-storage system reaches spent condition.On the one hand, exhaust may for excessive vehicle electrokinetic cell electricity
Cause high-voltage electrical apparatus loss or the distance increasing unit energy residual of Full Vehicle System, influence the overall energy efficiency of automobile；On the other hand,
The insufficient purpose that possibly can not obtain the reduction fuel consumption being pre-designed of vehicle electric quantity consumption, the ability of electrokinetic cell system
It is far from reaching using the limit.Therefore how to be obtained in the application of hybrid vehicle between suitable different-energy source
Power and energy stream distribution are one of root problems of energy management strategies.In actual applications, because driving cycle can not
Accurate precognition, therefore suitable energy management strategies are the key points for realizing hybrid vehicle energy-conserving and environment-protective.
Most commonly used four classes hybrid vehicle energy management strategies are studied at present：Rule-based control strategy, wink
When Optimal Control Strategy, global optimization control strategy and the ADAPTIVE CONTROL based on optimized algorithm.
The working mechanism of rule-based control strategy is：It is a series of with theory analysis and the setting of working experience intuition in advance
Vehicle program operation state values, its working region is divided.Worked according to the critical operating point of setting to judge vehicle
Region, so as to take corresponding control mode.Rule-based logic threshold algorithm is relatively easy, can be applied to real vehicle and control
Device, with reference to offline optimization as a result, it is possible to be optimized to parameter, so as to which the mode of operation for obtaining more reasonable, economic switches rule
Then.This kind of tactful biggest advantage is to be easy to Project Realization.But rule-based energy management strategies, regardless of whether entering
Went Optimization about control parameter, it still has some limitations in terms of the raising of fuel economy.
The equivalent fuel consumption of instantaneous optimization control strategy generally use is minimum or power loss min algorithm, by by two
The energy expenditure of energy source is carried out quantifying unification with ad hoc approach, calculates the instantaneous least energy consumption of vehicle.The strategy is in each step
It is optimal in length, but can not ensures optimal in whole driving cycle, and needs substantial amounts of floating-point operation and more accurate
Vehicle and dynamical system model, it is computationally intensive, realize difficult.This kind of energy management strategies obtain in Computer Simulation at present
Good fuel economy effect, but the not extensive use on real vehicle, because it is for real-time vehicle running state parameter
Collection, analysis and processing requirement it is higher, while the change of vehicle power system performance is to the real-time update shadow of basic database
Sound is larger.
Global optimization control strategy, know in advance running car it is all during under conditions of all duty parameters,
The global optimization of energy management can be realized.Global optimization pattern realizes optimization truly, but realizes this plan
Algorithm slightly is often all more complicated, and amount of calculation is also very big, and needs that all road informations are obtained ahead of time, in actual vehicle
Real-time control in hardly result in application.
ADAPTIVE CONTROL based on optimized algorithm, can be according to Current vehicle transport condition and road conditions automatic Prediction not
The power and energy requirement come in a period of time carrys out adjust automatically control parameter to adapt to the change of driving cycle.It is so-called adaptive
Should, it is exactly in each time step, adjusts part working method according to current driving conditions and road conditions requirement, calculated by optimizing
Method, on the premise of ensureing that object function optimizes, energy requirement is reasonably distributed to each energy source.It is although self-adaptive controlled
It is different to make the target function model optimized algorithm of strategy etc., but because Self Adaptive Control will gather substantial amounts of dynamical system in real time
System service data, calculates energy consumption, predicts following operating mode, optimization process is complicated, computationally intensive, causes it at present can not be in practice
It is applied.
The content of the invention
The brief overview of one or more aspects given below is to provide to the basic comprehension in terms of these.This general introduction is not
The extensive overview of all aspects contemplated, and the key or decisive key element for being both not intended to identify all aspects is also non-
Attempt to define the scope in terms of any or all.Its unique purpose is to provide the one of one or more aspects in simplified form
A little concepts think the sequence of more detailed description given later.
It is an object of the invention to solve the above problems, there is provided a kind of hybrid power system based on fuzzy logic algorithm
Energy management method, vehicle power demand can be calculated in real time automatically according to vehicle virtual condition and power distribution combines,
Ensure dynamic property and can improve the fuel economy of vehicle on the premise of meeting the needs of different users, while be also easy in real vehicle
Upper realization.
The technical scheme is that：Present invention is disclosed a kind of hybrid system energy pipe based on fuzzy logic algorithm
Reason method, it is characterised in that hybrid system includes entire car controller, energy source controller, electric machine controller and CAN,
The hybrid system energy management method includes：
Step 1：Self-test is carried out to entire car controller, energy controller and electric machine controller, step is entered if fault-free
2, failure handling mechanisms are entered if faulty；
Step 2：Entire car controller sends calling-on signal by CAN to energy source controller, drive motor controller
And obtain fuzzy logic algorithm and calculate required signal data；
Step 3：Entire car controller judges whether the required signal data of the fuzzy logic algorithm calculating received is complete, if
It is complete then enter step 4, return to step 2 if imperfect；
Step 4：Signal data of the entire car controller according to needed for calculating the fuzzy logic algorithm received, is calculated in real time
Vehicle demand power and/or vehicle dynamical system accessory power and/or energy source power output.
According to an embodiment of the hybrid power system energy management method based on fuzzy logic algorithm of the present invention, also wrap
Include：
Step 5：Amendment is adjusted to energy source power output using fuzzy logic algorithm, draws power output distribution group
Close；
Step 6：Entire car controller is based on power distribution combination and sends output work to each energy source controller by CAN
Rate allocation result, complete real-time adjustment of the entire car controller to energy source power output.
It is described according to an embodiment of the hybrid power system energy management method based on fuzzy logic algorithm of the present invention
Hybrid system also includes electrokinetic cell controller, distance increasing unit controller, vehicle power accessories, and its energy source includes power electric
Pond, distance increasing unit, entire car controller are controlled with electrokinetic cell controller, distance increasing unit controller, motor respectively by CAN
Device, the connection of vehicle power accessories, pass through between distance increasing unit and distance increasing unit controller, between electrokinetic cell and electrokinetic cell controller
CAN is connected, and distance increasing unit is connected by high-tension bus-bar with electrokinetic cell.
According to an embodiment of the hybrid power system energy management method based on fuzzy logic algorithm of the present invention, vehicle
Power accessories include the electricity consumption of instrument including vehicle heat dissipation subsystem, air conditioning subsystem and headlight, the electrical part of relay
Device.
According to an embodiment of the hybrid power system energy management method based on fuzzy logic algorithm of the present invention, step
Signal data in 2 includes current power battery SOC, SOC variation deltas SOC, range extender system residual fuel matter in the Δ t times
Measure mre, vehicle demand power Pvehicle, vehicle dynamical system accessory power Pauxiliary。
According to an embodiment of the hybrid power system energy management method based on fuzzy logic algorithm of the present invention, step
Vehicle demand power in 4 is calculated as follows：
Vehicle demand powerG
=mg, m are that vehicle is fully loaded with quality, and f is coefficient of rolling resistance, CDFor coefficient of air resistance, A is front face area of automobile, and V is automobile
Current vehicle speed, ηtFor overall transmission efficiency, δ is car mass conversion coefficient, and α is the travel angle of gradient, when α is less than certain value
When cos α=1, α=sin α=tan α=i, i be road grade, PauxiliaryFor vehicle power accessories system power.
According to an embodiment of the hybrid power system energy management method based on fuzzy logic algorithm of the present invention, vehicle
Power accessories system power PauxiliaryIt is the electrical equipment for including vehicle heat dissipation subsystem, air conditioning subsystem and headlight, relay
Part, instrument electrical appliance including summation of all low-voltage electrical appliance parts when all being worked with peak power.
According to an embodiment of the hybrid power system energy management method based on fuzzy logic algorithm of the present invention, step
The power output of distance increasing unit in 4 is calculated as follows in real time：
Distance increasing unit power outputWherein EreFor residual fuel
The electric energy that can be converted to by distance increasing unit, T be electrokinetic cell according to the last period state-of-charge SOC consumption rate estimate can
The time persistently used, M are the fuel used calorific values of distance increasing unit, and η is that range extender system is converted the fuel into and turned for the energy of electric energy
Change efficiency, SOCtFor the current state-of-charge of electrokinetic cell, SOCminThe cutoff allowed by electrokinetic cell, Δ t are sampling week
Phase, Δ SOC be the sampling period in SOC variable quantities, mreFor the residual mass of current range extender system fuel.
According to an embodiment of the hybrid power system energy management method based on fuzzy logic algorithm of the present invention, step
The adjustment amendment of 5 energy source power output is as follows：
Wherein PreFor the power output of the distance increasing unit after adjustment, Pre_calFor the output work for the distance increasing unit being calculated in real time
Rate, Pre_maxFor the maximum sustainable power output of distance increasing unit, Pre_minFor the minimum license power output of distance increasing unit；
Electrokinetic cell power output Pbattery=Pvehicle-Pre。
According to an embodiment of the hybrid power system energy management method based on fuzzy logic algorithm of the present invention, the energy
Amount control method includes the energy management strategies suitable for extended-range electric vehicle hybrid power system.
Present invention contrast prior art has following beneficial effect：
1) present invention can provide the energy expenditure rate of detection Current vehicle and each energy in real time based on fuzzy logic algorithm
The real-time status in amount source, the power request for predicting following vehicle is calculated by fuzzy logic, according to the result of calculation of fuzzy logic
Adjust the power output of each energy source in real time with corresponding logic rules, real-time is good；
2) the fuzzy logic calculation formula in the present invention and logic rules have the effect that：A) when electrokinetic cell electricity disappears
Distance increasing unit power output can be improved when consuming too fast in real time, distance increasing unit power output can be reduced when electric quantity consumption rate is relatively low in real time, kept away
Exempt from electrokinetic cell high current charge-discharge, take into account electrokinetic cell life-span and energy conversion efficiency；B) patrolled according to corresponding obscure
The inefficient working region of range extender system can be avoided by collecting rule, improve vehicle fuel economy；
3) fuzzy logic algorithm solves the power battery for hybrid electric vehicle electricity mentioned in background technology and excessively disappeared
Consumption either consumes the problem of insufficient；
4) fuzzy logic algorithm requires relatively low to controller hardware, is easy to realize on vehicle；
5) energy management algorithm of the present invention can be applied to fuel cell-battery, and internal combustion engine-battery is interior
The new-energy automobile hybrid power system of the diversified forms such as combustion engine-super capacitor, there is good autgmentability.
Brief description of the drawings
Fig. 1 shows the topological structure schematic diagram for being applicable the range-extending type hybrid electric vehicle dynamical system of the present invention.
Fig. 2 shows the preferable implementation of the hybrid power system energy management method based on fuzzy logic algorithm of the present invention
The flow chart of example.
Embodiment
After the detailed description of embodiment of the disclosure is read in conjunction with the following drawings, it better understood when the present invention's
Features described above and advantage, but the invention is not limited in any way.In the accompanying drawings, each component is not necessarily drawn to scale, and
And the component with similar correlation properties or feature may be with same or like reference.It should be pointed out that pair
For one of ordinary skill in the art, without departing from the inventive concept of the premise, some deformations can also be made and changed
Enter, belong to protection scope of the present invention.
First illustrating the general plotting of the hybrid power system energy management method of the present invention, it is based on fuzzy logic algorithm,
The Capacity Management rule that the energy management strategies of hybrid power system are reduced to one group of multi input, singly exported by the fuzzy logic algorithm
Then, using fuzzy logic calculation according to electrokinetic cell SOC, SOC variation deltas SOC, range extender system residue in the Δ t times
Fuel mass mre, vehicle demand power Pvehicle, vehicle dynamical system accessory power PauxiliaryEtc. parameter by calculate in real time come
The power output of hybrid power system energy source is controlled, the fuel-economy of high vehicle is provided on the premise of user's request is met
Property.
Topological structure in conjunction with Fig. 1 descriptions using the extended-range electric vehicle hybrid power system of the method for the present embodiment.
As shown in figure 1, dynamical system includes electrokinetic cell 1, distance increasing unit 2, range extender system 3, motor 4, entire car controller VMS
5th, electrokinetic cell controller BMS 6, distance increasing unit controller RES 7, drive motor controller PEU 8, vehicle dynamical system annex
9th, CAN 10.
Entire car controller VMS 5 connects distance increasing unit controller RES 7 and electrokinetic cell controller by CAN 10 respectively
BMS 6, drive motor controller PEU 8 and vehicle dynamical system annex 9.Distance increasing unit 2 is connected with distance increasing unit controller RES 7,
Electrokinetic cell 1 is connected with electrokinetic cell controller BMS 6, and distance increasing unit 2 is connected by high-tension bus-bar with electrokinetic cell 1.
The control parameter of energy management strategies in entire car controller VMS 5 and is used as the dynamic of energy source by CAN 10
Data interaction is completed between power battery controller 6 and distance increasing unit controller 7.Entire car controller VMS 5 obtains 10 from CAN and obtains energy
Fuzzy logic algorithm formula, which is provided, after data needed for buret reason policy calculation calculates distance increasing unit power output, then it is total by CAN
Power output combination is sent to the controller (electrokinetic cell controller 6 and distance increasing unit controller 7) of each energy source by line 10, with
Complete the real-time adjustment of dynamical system energy source power.
Vehicle dynamical system annex 9 includes the electrical equipment such as vehicle heat dissipation subsystem, air conditioning subsystem and headlight, relay
The electrical appliance power consumption such as part, instrument.
Based on the extended-range electric vehicle hybrid power system shown in Fig. 1, the mixing of the invention based on fuzzy logic algorithm
The flow of the preferred embodiment of dynamical system energy management method is as shown in Figure 2.
In step s 201, entire car controller VMS, drive motor controller PEU, electrokinetic cell controller BMS, distance increasing unit
Controller RES carries out self-test to its responsible subsystem respectively, determines whether failure, enters each system ready state if nothing,
Perform step 203；If so, then carry out failure handling mechanisms step S202.
In step 203, entire car controller VMS by CAN to electrokinetic cell controller BMS, distance increasing unit controller
RES, drive motor controller PEU send calling-on signal, therefrom obtain energy management strategies and calculate required signal data.
Required signal data includes current power battery SOC, and (State of Charge, i.e., power accumulator is charged
State, sign is that battery uses the residual capacity after a period of time), SOC variation deltas SOC, distance increasing unit system in the Δ t times
Residual fuel quality of uniting mre, vehicle demand power Pvehicle, vehicle dynamical system accessory power Pauxiliary。
In step 204, whether the signal data that entire car controller VMS judgements receive is complete, if so, then performing step
205；If nothing, return to step 203.
In step 205, entire car controller VMS calculates demand data according to the energy management strategies received, passes through reality
When be calculated vehicle request power Pvehicle, distance increasing unit power output P is drawn by fuzzy logic algorithm and respective rulereWith
Electrokinetic cell power output Pbattery, show that power distribution combines P by adjustment in real time is finalvehicle=F (Pbattery, Pre,
Pauxiliary), subsequently into step 206.
The fuzzy logic algorithm being related in step 205 is as follows：
A) vehicle request power
G=mg, m are that vehicle is fully loaded with quality, and f is coefficient of rolling resistance, ηtFor vehicle transmission efficiency, α is the gradient, CDFor air drag system
Number, A is front face area of automobile, and V is automobile current vehicle speed, and δ is car mass conversion coefficient, and the angle of gradient of usual travel is not
Cos α=1, α=sin α=tan α=i, i are road grade when big, PauxiliaryFor the accessory power of vehicle dynamical system, mainly
For vehicle heat dissipation subsystem, air conditioning subsystem and headlight, the electrical part of relay, instrument panel lamp electrical appliance, PauxiliaryValue
Summation when all being worked for above-mentioned all low-voltage electrical appliance parts with peak power；
B) the real-time calculated value of distance increasing unit power output
Wherein EreThe electric energy that can be converted to by distance increasing unit for residual fuel, T are electrokinetic cell according to the last period SOC's
The sustainable time used that consumption rate estimates, M are the fuel used calorific value of distance increasing unit (xx MJ/kg), and η is distance increasing unit system
System converts the fuel into the energy conversion efficiency (%) for electric energy, SOCtFor the current state-of-charge of electrokinetic cell, SOCminFor power electric
The cutoff that pond is allowed, Δ t are the sampling period (h), and Δ SOC is the SOC variable quantities in the sampling period, mreCurrent distance increasing unit system
The residual mass of system fuel.
In step 206, the energy source power output being calculated in real time is adjusted by fuzzy logic algorithm and repaiied
Just, combined with obtaining power distribution.It is specific as follows：If a) Pre_calMore than the maximum sustainable power P of range extender systemre_max,
Then can only be with Pre_maxOutput；If Pre_calLess than the minimum license power output of range extender system, then with Pre_minOutput.Wherein
Pre_minFor the power points according to corresponding to the inefficient area that range extender system characteristic curve defines.By taking engine as an example, Pre_minFor
Engine is avoided to enter power points corresponding to low rotation speed area.
Summarizing formula is：
Cell output Pbattery=Pvehicle-Pre。
In step 207, entire car controller VMS by CAN to electrokinetic cell controller BMS and distance increasing unit controller
RES transmit power output results, complete entire car controller VMS and each energy source power output of dynamical system is distributed.
Although for make explanation simplify the above method is illustrated and is described as a series of actions, it should be understood that and understand,
The order that these methods are not acted is limited, because according to one or more embodiments, some actions can occur in different order
And/or with from it is depicted and described herein or herein it is not shown and describe but it will be appreciated by those skilled in the art that other
Action concomitantly occurs.
Those skilled in the art will further appreciate that, with reference to the embodiments described herein come the various illustratives that describe
Logic plate, module, circuit and algorithm steps can be realized as electronic hardware, computer software or combination of the two.To be clear
Explain to Chu this interchangeability of hardware and software, various illustrative components, frame, module, circuit and step be above with
Its functional form makees vague generalization description.Such feature be implemented as hardware or software depend on concrete application and
Put on the design constraint of total system.Technical staff can be realized described for every kind of application-specific with different modes
Feature, but such realize that decision-making should not be interpreted to cause departing from the scope of the present invention.
General place can be used with reference to various illustrative logic plate, module and the circuits that presently disclosed embodiment describes
Reason device, digital signal processor (DSP), application specific integrated circuit (ASIC), field programmable gate array (FPGA) other are compiled
Journey logical device, discrete door or transistor logic, discrete nextport hardware component NextPort or its be designed to carry out function described herein
Any combinations are realized or performed.General processor can be microprocessor, but in alternative, the processor can be appointed
What conventional processor, controller, microcontroller or state machine.Processor is also implemented as the combination of computing device, example
As the combination of DSP and microprocessor, multi-microprocessor, the one or more microprocessors to be cooperated with DSP core or it is any its
His such configuration.
It can be embodied directly in hardware, in by processor with reference to the step of method or algorithm that embodiment disclosed herein describes
Embodied in the software module of execution or in combination of the two.Software module can reside in RAM memory, flash memory, ROM and deposit
Reservoir, eprom memory, eeprom memory, register, hard disk, removable disk, CD-ROM or known in the art appoint
In the storage medium of what other forms.Exemplary storage medium is coupled to processor to enable the processor from/to the storage
Medium is read and write-in information.In alternative, storage medium can be integrated into processor.Processor and storage medium can
Reside in ASIC.ASIC can reside in user terminal.In alternative, processor and storage medium can be used as discrete sets
Part is resident in the user terminal.
In one or more exemplary embodiments, described function can be in hardware, software, firmware or its any combinations
Middle realization.If being embodied as computer program product in software, each function can be used as the instruction of one or more bars or generation
Code storage is transmitted on a computer-readable medium or by it.Computer-readable medium includes computer-readable storage medium and communication
Both media, it includes any medium for facilitating computer program to shift from one place to another.Storage medium can be can quilt
Any usable medium that computer accesses.It is non-limiting as example, such computer-readable medium may include RAM, ROM,
EEPROM, CD-ROM or other optical disc storage, disk storage or other magnetic storage apparatus can be used to carrying or store instruction
Or desirable program code and any other medium that can be accessed by a computer of data structure form.Any connection is also by by rights
Referred to as computer-readable medium.For example, if software is using coaxial cable, fiber optic cables, twisted-pair feeder, digital subscriber line
(DSL) or the wireless technology of such as infrared, radio and microwave etc passes from web site, server or other remote sources
Send, then the coaxial cable, fiber optic cables, twisted-pair feeder, DSL or such as infrared, radio and microwave etc is wireless
Technology is just included among the definition of medium.Disk (disk) and dish (disc) as used herein include compact disc
(CD), laser disc, laser disc, digital versatile disc (DVD), floppy disk and blu-ray disc, which disk (disk) are often reproduced in a manner of magnetic
Data, and dish (disc) laser reproduce data optically.Combinations of the above should also be included in computer-readable medium
In the range of.
Offer is for so that any person skilled in the art all can make or use this public affairs to being previously described for the disclosure
Open.Various modifications to the disclosure all will be apparent for a person skilled in the art, and as defined herein general
Suitable principle can be applied to spirit or scope of other variants without departing from the disclosure.Thus, the disclosure is not intended to be limited
Due to example described herein and design, but should be awarded and principle disclosed herein and novel features phase one
The widest scope of cause.
Claims (9)
1. a kind of hybrid system energy management method based on fuzzy logic algorithm, it is characterised in that hybrid system includes
Entire car controller, energy source controller, electric machine controller and CAN, the hybrid system energy management method include：
Step 1：Self-test is carried out to entire car controller, energy controller and electric machine controller, step 2 is entered if fault-free, if
It is faulty then to enter failure handling mechanisms；
Step 2：Entire car controller sends calling-on signal to energy source controller, drive motor controller by CAN and obtained
Fuzzy logic algorithm is taken to calculate required signal data；
Step 3：Entire car controller judges whether the required signal data of the fuzzy logic algorithm calculating received is complete, if completely
Then enter step 4, return to step 2 if imperfect；
Step 4：Signal data of the entire car controller according to needed for calculating the fuzzy logic algorithm received, calculates vehicle in real time
Demand power and/or vehicle dynamical system accessory power and/or energy source power output；
Vehicle demand power wherein in step 4 is calculated as follows：
Vehicle demand powerG=
Mg, m are that vehicle is fully loaded with quality, and f is coefficient of rolling resistance, CDFor coefficient of air resistance, A is front face area of automobile, and V works as automobile
Preceding speed, ηtFor overall transmission efficiency, δ is car mass conversion coefficient, and α is the travel angle of gradient, when α is less than certain value
Cos α=1, α=sin α=tan α=i, i are road grade, PauxiliaryFor vehicle power accessories system power.
2. the hybrid power system energy management method according to claim 1 based on fuzzy logic algorithm, its feature exist
In, in addition to：
Step 5：Amendment is adjusted to energy source power output using fuzzy logic algorithm, draws power output distribution combination；
Step 6：Entire car controller is based on power distribution combination and sends power output point to each energy source controller by CAN
With result, real-time adjustment of the entire car controller to energy source power output is completed.
3. the hybrid power system energy management method according to claim 2 based on fuzzy logic algorithm, its feature exist
In the hybrid system also includes electrokinetic cell controller, distance increasing unit controller, vehicle power accessories, and its energy source includes
Electrokinetic cell, distance increasing unit, entire car controller are electric with electrokinetic cell controller, distance increasing unit controller, driving respectively by CAN
Machine controller, the connection of vehicle power accessories, between distance increasing unit and distance increasing unit controller, electrokinetic cell and electrokinetic cell controller it
Between connected by CAN, distance increasing unit is connected by high-tension bus-bar with electrokinetic cell.
4. the hybrid power system energy management method according to claim 3 based on fuzzy logic algorithm, its feature exist
In vehicle power accessories include vehicle heat dissipation subsystem, air conditioning subsystem and headlight, the electrical part of relay including instrument
Electrical appliance.
5. the hybrid power system energy management method according to claim 4 based on fuzzy logic algorithm, its feature exist
In the signal data in step 2 includes current power battery SOC, SOC variation deltas SOC, range extender system remain in the Δ t times
Remaining fuel mass mre, vehicle demand power Pvehicle, vehicle dynamical system accessory power Pauxiliary。
6. the hybrid power system energy management method according to claim 5 based on fuzzy logic algorithm, its feature exist
In vehicle power accessories system power PauxiliaryIt is to include vehicle heat dissipation subsystem, air conditioning subsystem and headlight, relay
Electrical part, instrument electrical appliance including summation of all low-voltage electrical appliance parts when all being worked with peak power.
7. the hybrid power system energy management method according to claim 6 based on fuzzy logic algorithm, its feature exist
In the power output of the distance increasing unit in step 4 is calculated as follows in real time：
Distance increasing unit power outputWherein ErePass through for residual fuel
The electric energy that distance increasing unit can be converted to, T estimate sustainable for electrokinetic cell according to the last period state-of-charge SOC consumption rate
The time used, M are the fuel used calorific values of distance increasing unit, and η is that range extender system converts the fuel into energy conversion effect for electric energy
Rate, SOCtFor the current state-of-charge of electrokinetic cell, SOCminThe cutoff allowed by electrokinetic cell, Δ t are the sampling period, Δ
SOC be the sampling period in SOC variable quantities, mreFor the residual mass of current range extender system fuel.
8. the hybrid power system energy management method according to claim 7 based on fuzzy logic algorithm, its feature exist
In the adjustment amendment of the energy source power output of step 5 is as follows：
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Wherein PreFor the power output of the distance increasing unit after adjustment, Pre_calFor the power output for the distance increasing unit being calculated in real time,
Pre_maxFor the maximum sustainable power output of distance increasing unit, Pre_minFor the minimum license power output of distance increasing unit；
Electrokinetic cell power output Pbattery=Pvehicle-Pre。
9. the hybrid power system energy management method according to claim 1 based on fuzzy logic algorithm, its feature exist
In the energy management method includes the energy management strategies suitable for extended-range electric vehicle hybrid power system.
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| CN106740822A (en) * | 2017-02-14 | 2017-05-31 | 上汽大众汽车有限公司 | Hybrid power system and its energy management method |
| CN108363855B (en) * | 2018-02-02 | 2021-06-25 | 杭州电子科技大学 | Fuel cell and super capacitor system optimization method based on road condition recognition |
| CN110103949B (en) * | 2019-04-18 | 2021-04-23 | 浙江吉利控股集团有限公司 | Fault processing method and device for hybrid vehicle and vehicle |
| CN110228482B (en) * | 2019-05-15 | 2020-07-03 | 吉林大学 | Hybrid power bus station area control method based on intelligent traffic information |
| CN110414042B (en) * | 2019-06-14 | 2023-05-05 | 青岛科技大学 | Ship cluster situation analysis method under conflict meeting situation |
| CN112356818B (en) * | 2019-10-23 | 2021-12-21 | 万向集团公司 | Function safety monitoring method for range extender control system |
| CN111976458B (en) * | 2019-12-16 | 2021-11-26 | 中北大学 | Series type severe hybrid power engineering machinery transmission system and control method thereof |
| CN111660827B (en) * | 2020-06-03 | 2021-07-06 | 东风小康汽车有限公司重庆分公司 | State machine for range-extended electric automobile and range-extended electric automobile |
| CN112109594B (en) * | 2020-08-31 | 2021-12-28 | 上汽大众汽车有限公司 | Energy management control method and system for hybrid vehicle |
| CN113859214B (en) * | 2021-09-28 | 2023-03-14 | 清华大学 | Method and device for controlling dynamic energy efficiency of engine of hybrid power system |
| CN114103732B (en) * | 2021-12-16 | 2023-10-24 | 上汽大众汽车有限公司 | Charging and heating method and system for power battery of electric vehicle |
| CN117311330B (en) * | 2023-11-29 | 2024-03-15 | 江西五十铃汽车有限公司 | Control method and system of whole vehicle controller, storage medium and electronic equipment |
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