CN107472038A - Hybrid vehicle energy management method based on hcci engine - Google Patents
Hybrid vehicle energy management method based on hcci engine Download PDFInfo
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- CN107472038A CN107472038A CN201710601345.6A CN201710601345A CN107472038A CN 107472038 A CN107472038 A CN 107472038A CN 201710601345 A CN201710601345 A CN 201710601345A CN 107472038 A CN107472038 A CN 107472038A
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
- B60L50/00—Electric propulsion with power supplied within the vehicle
- B60L50/10—Electric propulsion with power supplied within the vehicle using propulsion power supplied by engine-driven generators, e.g. generators driven by combustion engines
- B60L50/15—Electric propulsion with power supplied within the vehicle using propulsion power supplied by engine-driven generators, e.g. generators driven by combustion engines with additional electric power supply
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/60—Other road transportation technologies with climate change mitigation effect
- Y02T10/70—Energy storage systems for electromobility, e.g. batteries
-
- 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
- Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
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- Engineering & Computer Science (AREA)
- Power Engineering (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Electrical Control Of Ignition Timing (AREA)
- Combined Controls Of Internal Combustion Engines (AREA)
Abstract
A kind of hybrid power energy management method based on hcci engine is claimed in the present invention, is related to new-energy automobile field.The present invention is used as the power source of hybrid vehicle by the use of hcci engine.It can not be surveyed in view of hcci engine ignition timing, the present invention opens and closes timing, engine speed, MAT, distributive value as input using inlet and exhaust valve, builds the ignition timing of neural network prediction hcci engine；Using the opening and closing moment of VVT control engine breathing door, the waste gas recompression of hcci engine is realized, so as to by gaseous mixture compression ignition；Hcci engine waste gas is introduced into Stirling engine again, power battery charging is similarly using Stirling engine acting, so as to comprehensively utilize the energy of fuel, reaches the requirement of energy-conservation and environmental protection.
Description
Technical field
New-energy automobile field of the present invention, particularly a kind of hybrid vehicle.
Background technology
With continuous exhausted and people's environmental protection consciousness the enhancing of oil, new energy vapour of the people to energy-conserving and environment-protective
Car proposes more requirements.In this case, the substitute products of the orthodox car such as hybrid vehicle, electric automobile are not
It is disconnected to emerge in large numbers.Before the problems such as continuation of the journey in pure electric automobile battery, charging is not fully solved, hybrid vehicle is good
Selection.Hybrid vehicle carries engine and power motor simultaneously, and when electrokinetic cell not enough power supply, engine driving generates electricity
Machine is power battery charging, and electrokinetic cell provides energy for power motor and drives motor racing, when automobile needs high-power output
When, engine can cooperate with power motor, drive automobile jointly.The engine of hybrid vehicle is all using tradition at present
The diesel engine (CI) of engine, i.e. spark-ignition gasoline machine (SI) or compression and combustion, although being the advantages of hybrid vehicle
Engine can be operated in best efficiency point, engine relative energy-saving, but the thermal efficiency of both engines all than relatively limited, relatively
At most also with regard to more than 40%, be cooled water, waste gas, casing wall of most heats is taken away, and causes pole for the thermal efficiency of higher diesel engine
Big energy dissipation.
Average inflation compressing ignition (HCCI) technology is born in 1897, has nonflame speciality and highly diluted ability so that
Burning can be carried out at a lower temperature, it is possible to reduce NOX and PM formation, reduce CO and HC discharge.In addition, HCCI exists
Worked under non-air throttle state, the pumping loss of engine can be reduced to a great extent, improve fuel efficiency up to 30%, effectively
Reduce fuel consumption.In consideration of it, HCCI is acknowledged as combustion technology of new generation, it is a quite promising technology, can reducing
Fuel efficiency is further improved while discharge, is that this present invention considers to be used as the dynamic of hybrid vehicle by the use of hcci engine
Charged for battery in power source.
At present plug-in and vehicular can be divided into according to hybrid power automobile battery charging modes.Plug-in hybrid
Automobile is charged using off-board recharging device to battery, and distance travelled is shorter after once charging；Vehicular hybrid vehicle is then profit
Battery is charged with engine and onboard charger, its volume is big, and oil consumption is high.Patent [CN201110268778.7] discloses one
Kind of compact-sized, the charging engine of hybrid electric vehicle of small volume, alleviate hybrid electric vehicle and sail that mileage is short and charging
The problem of engine volume is big, weight is big, but without the present situation that change engine efficiency is low, discharge is high, therefore the present invention will adopt
Charging generator is used as by the use of hcci engine.And there is temperature height, the big spy of heat for hybrid electric vehicle engine waste gas
Point, great energy dissipation is caused to air by waste gas is in line.
The content of the invention
It is low for the prior art hybrid power engine thermal efficiency, discharge the shortcomings that high, present invention design one kind is based on
The hybrid vehicle energy management method of hcci engine, power battery for hybrid electric vehicle is used as by the use of hcci engine
Power source, while be power battery charging using the exhaust gas driven Stirling engine of hcci engine, realize hybrid power vapour
Car energy management.
The technical scheme that the present invention solves above-mentioned technical problem is to provide one kind based on average inflation compressing ignition HCCI hairs
The hybrid vehicle and its EMS of motivation, including hcci engine, Stirling engine, generator A, generator
B, battery and motor, the waste gas of hcci engine connects driving Stirling engine by pipeline, for driving engine B,
Hcci engine direct drive generator A, generator A, B are power battery charging, when electrokinetic cell needs charging, HCCI
Driven by engine generator A is power battery charging, meanwhile, the exhaust gas driven Stirling engine of hcci engine, Stirling
It is power battery charging that engine drives generator B again, and electrokinetic cell provides energy for the power motor of hybrid vehicle and driven
Dynamic motor, controls actuator drives motor racing.
Wherein, the exhaust gas driven Stirling engine of hcci engine further comprises：Utilize VVT
The ignition timing of the timing control hcci engine of inlet valve and exhaust valve is controlled, realizes that waste gas recompresses, so as to by gaseous mixture
Compression ignition.
Further, the igniting of hcci engine is controlled to further comprise：Establish with inlet and exhaust valve timing, inlet manifold
Pressure, MAT, engine speed, distributive value are input layer, three layers using hcci engine ignition timing as output
For BP neural network to predict the ignition timing of hcci engine, input signal inputs input layer first, then by hidden layer, most
After reach output layer.Input layer includes 8 neurodes of input vector, and hidden layer includes hidden layer neuron activation function
(), hidden layer neuron threshold θj4 neuron nodes, output layer include by output layer neuron activation primitive ψ
() structure output vector y 1 neuron node, wherein, the threshold θ of output layer neuron, input layer is to implying
Connection weight ω between layer neuronij, hidden layer neuron to the connection weight ω between output layer neuronj。
According to formulaCalculate the input signal net of j-th of neuron node of hidden layerj；Root
According to formulaCalculate the output signal o of j-th of neurode of hidden layerj；According to
Formula：Calculate the defeated of output layer neuron node
Enter signal net；According to formulaCalculate output layer neuromere
The output signal y of point, the regulation and control of the ignition timing to hcci engine are realized by output vector.
The present invention also proposes a kind of hybrid vehicle and its energy based on average inflation compressing ignition hcci engine
Management method, including step, the waste gas of hcci engine connects driving Stirling engine by pipeline, for driving engine
B, hcci engine direct drive generator A, generator A, B are power battery charging, when electrokinetic cell needs charging,
It is power battery charging that hcci engine, which drives generator A, meanwhile, the exhaust gas driven Stirling engine of hcci engine, this
It is power battery charging that special woods engine drives generator B again, and electrokinetic cell provides energy for the power motor of hybrid vehicle
Drive motor is measured, controls actuator drives motor racing.
The electrokinetic cell of hybrid vehicle for motor provide energy drive motor racing, when electrokinetic cell electricity not
When sufficient, it is power battery charging to drive generator A using hcci engine, meanwhile, the waste gas of hcci engine is sent out for Stirling
Motivation provides heat, and driving generator B is power battery charging；Inlet valve and exhaust valve are controlled using VVT
Timing, effectively control the igniting of hcci engine, realize that waste gas recompresses, so as to which by gaseous mixture compression ignition, hcci engine drives
Dynamic generator is power battery charging.
There is temperature height, heat for the present situation that engine efficiency is low, discharge is high, and hybrid electric vehicle engine waste gas
The characteristics of big is measured, causes great energy dissipation to air by waste gas is in line.The present invention is sent out using hcci engine as charging
Motivation, using the waste gas of hcci engine Stirling will be driven to start on the basis of hcci engine is power battery charging
It is power battery charging that machine, which drives the generator of another, so as to which that fully improves engine utilizes specific energy.
Brief description of the drawings
Hybrid vehicle energy systems of the Fig. 1 based on hcci engine；
Hybrid vehicle energy management methods of the Fig. 2 based on hcci engine；
The BP neural network model of Fig. 3 ignition timing prediction.
Embodiment
In order to make the purpose , technical scheme and advantage of the present invention be clearer, below in conjunction with accompanying drawing and example, to this
Invention is further described.
Fig. 1 is that the hybrid vehicle energy system based on average inflation compressing ignition hcci engine forms schematic diagram.
For hcci engine high efficiency, the characteristic of low emission, the hybrid vehicle energy system of the invention based on hcci engine
Including hcci engine, Stirling engine, generator A, generator B, battery and motor.The waste gas of hcci engine passes through
Pipeline connection driving Stirling engine, for driving engine B；Hcci engine is by mechanically connecting driving generator A；Hair
Motor A, B connect battery by being electrically connected drive motor, control transmission device.
The detailed content of the present invention is explained further below by Fig. 2.
Hcci engine is the power resources of whole hybrid vehicle, when electrokinetic cell needs charging, starts HCCI
Engine, hcci engine driving generator A, charges to battery；It can not be surveyed in view of hcci engine ignition timing, this
Invention opens and closes timing, engine speed, air- distributor pressure, MAT, distributive value to be defeated using inlet and exhaust valve
Enter, build neutral net and repeatedly train, the ignition timing of prediction output hcci engine.By ignition timing desired value and prediction
The difference input proportional-integral derivative controller (PID, Proportion Integration Differentiation) of value,
By controlling distributive value, inlet and exhaust valve to open and close timing, the regulation and control of the ignition timing to hcci engine are realized；And HCCI
Engine utilizes changeable air valve technology, and member-retaining portion waste gas participates in combustion process, can strengthen the high efficiency of hcci engine again
With low emission characteristic；After hcci engine operating, Stirling engine collects the energy in hcci engine tail gas, and drives hair
Motor B is stored in the battery in the form of electric energy；When charging is complete, hcci engine is closed.
Fig. 3 is the BP neural network structural model of ignition timing prediction, and input signal is first inputted to input layer, Ran Houjing
Hidden layer is crossed, finally reaches output layer.Input signal includes：IO Intake Valve Opens timing u1, exhauxt valve opens timing u2, inlet valve
Closure timings u3, exhaust valve closing timing u4, engine speed u5, air- distributor pressure u6, MAT u7, distributive value
u8.Wherein, input layer includes 8 neurodes (i=1,2,3,4,5,6,7,8), input vector u=(u1, u2, u3, u4, u5,
u6, u7, u8)T∈R8；(T is the transposition of matrix, and R is real number) hidden layer includes 4 neuron nodes (j=1,2,3,4),
() represents the activation primitive of hidden layer neuron, θjRepresent the threshold value of hidden layer neuron；Output layer includes 1 neuron section
Point (k=1), output vector y, ψ () represent the activation primitive of output layer neuron, and θ represents the threshold value of output layer neuron.
ωijRepresent input layer to the connection weight between hidden layer neuron；ωjRepresent hidden layer neuron to output layer god
Through the connection weight between member.
In the communication process forward of input signal, according to the connection weight between the threshold value of each layer neuron and each layer
Value, the input/output signal of hidden layer and output layer is calculated respectively.The output vector y of output layer is obtained, it is real by output vector
The now regulation and control of the ignition timing to hcci engine.
The input signal net of j-th of neuron node of hidden layerjFor
In formula, ω represents that input layer represents output layer neuron to the connection weight between hidden layer neuron, θ
Threshold value, u is input vector.
The output signal o of j-th of neurode of hidden layerjFor
In formula,() represents the activation primitive of hidden layer neuron.
The input signal net of output layer neuron node is
The output signal y of output layer neurode is
In formula, ψ () represents the activation primitive of output layer neuron.
In the back-propagation process of error, from each layer of error of output layer backwards calculation, according to gradient descent algorithm more
The connection value and threshold value of new each layer, make the reality output of network close to desired output.
If training sample set includes P training sample, then for each training sample p (p=1,2..., p), error
Quadratic form criterion function is
Network is to the global error function of P training sample
Wherein E(p)Represent single sample error, E represent all sample errors it is cumulative and；d(p)And y(p)Input is represented respectively
When training sample is p, the desired output and reality output of output layer neuron node.
The connection weight and threshold value of network, the connection weight of hidden layer to output layer are successively updated according to gradient descent algorithm
Correction amount ωj, output layer threshold value correction amount θ, the connection weight correction amount ω of input layer to hidden layerij, output layer threshold
It is worth correction amount θj：
The connection weight of hidden layer to output layer adjusts formula
Output layer adjusting thresholds formula is
Input layer adjusts formula to hidden layer connection weight
Hidden layer threshold value adjusts formula
And because
Finally draw formula：
ωj(k+1)=η δ oj+ωj(k) (17)
θ (k+1)=η δ+θ (k) (19)
ωij(k+1)=η δjui+ωij(k) (21)
θj(k+1)=η δj+θj(k) (23)
Wherein η is learning rate, and k is frequency of training, δ and δjThe error signal of output layer and hidden layer is represented respectively.
The present invention considers that the ignition timing of hcci engine can not survey, and is sent out according to hcci engine ignition timing and HCCI
The rotating speed of motivation, air- distributor pressure, distributive value etc. are relevant, and the present invention is with inlet and exhaust valve timing, air- distributor pressure, air inlet discrimination
Pipe temperature, engine speed, distributive value is input, using three layers of BP neural network that hcci engine ignition timing is output with pre-
Survey the ignition timing of engine.
Claims (10)
1. a kind of hybrid vehicle and its EMS based on average inflation compressing ignition hcci engine, its feature
It is, including hcci engine, Stirling engine, generator A, generator B, battery and motor, hcci engine give up
Gas connects driving Stirling engine by pipeline, for driving engine B, hcci engine direct drive generator A, generates electricity
Machine A, B are power battery charging, and when electrokinetic cell needs charging, hcci engine drives generator A to be filled for electrokinetic cell
Electricity, meanwhile, the exhaust gas driven Stirling engine of hcci engine, it is electrokinetic cell that Stirling engine drives generator B again
Charging, electrokinetic cell provide energy drive motor for the power motor of hybrid vehicle, control actuator drives automobile
Motion.
2. system according to claim 1, it is characterised in that the exhaust gas driven Stirling engine of hcci engine enters one
Step includes：The igniting of the timing control hcci engine of inlet valve and exhaust valve is controlled using VVT, is realized
Waste gas recompresses, so as to by gaseous mixture compression ignition.
3. system according to claim 2, it is characterised in that control the igniting of hcci engine to further comprise：Establish
The ignition timing of three layers of BP neural network prediction hcci engine comprising input layer, hidden layer, output layer, with inlet and exhaust valve just
When, air- distributor pressure, MAT, engine speed, distributive value be input layer, using hcci engine ignition timing as
Output, input signal input input layer, then by hidden layer, finally reach output layer first.
4. system according to claim 3, it is characterised in that input layer includes 8 neurodes of input vector, implies
Layer includes hidden layer neuron activation functionHidden layer neuron threshold θ j 4 neuron nodes, output layer include
By activation primitive ψ () the structure output vectors y of output layer neuron 1 neuron node, wherein, output layer neuron
Threshold θ, input layer to the connection weight ω ij between hidden layer neuron, hidden layer neuron to output layer neuron
Between connection weight ω j.
5. system according to claim 3, it is characterised in that according to formulaCalculate hidden layer jth
The input signal net of individual neuron nodej；According to formulaCalculate hidden layer jth
The output signal o of individual neurodej；According to formula：Calculate
The input signal net of output layer neuron node；According to formula
Calculate the output signal y of output layer neurode.
6. a kind of hybrid vehicle and its energy management method based on average inflation compressing ignition hcci engine, its feature
It is, the waste gas of hcci engine connects driving Stirling engine by pipeline, for driving engine B, hcci engine
Direct drive generator A, generator A, B are power battery charging, and when electrokinetic cell needs charging, hcci engine drives
Generator A is power battery charging, meanwhile, the exhaust gas driven Stirling engine of hcci engine, Stirling engine drives again
Dynamic generator B is power battery charging, and electrokinetic cell provides energy drive motor for the power motor of hybrid vehicle, control
Actuator drives motor racing processed.
7. according to the method for claim 6, it is characterised in that the exhaust gas driven Stirling engine of hcci engine enters one
Step includes：The ignition timing of the timing control hcci engine of inlet valve and exhaust valve is controlled using VVT,
Realize that waste gas recompresses, so as to by gaseous mixture compression ignition.
8. according to the method for claim 7, it is characterised in that control the ignition timing of hcci engine to further comprise：
Establish three layers of BP neural network comprising input layer, hidden layer, output layer and predict the ignition timing of hcci engine, with intake and exhaust
Door timing, air- distributor pressure, MAT, engine speed, distributive value are input layer, with hcci engine igniting just
When for output, input signal inputs input layer, then by hidden layer, finally reaches output layer first.
9. according to the method for claim 8, it is characterised in that input layer includes 8 neurodes of input vector, implies
Layer includes hidden layer neuron activation functionHidden layer neuron threshold θj4 neuron nodes, output layer includes
By activation primitive ψ () the structure output vectors y of output layer neuron 1 neuron node, wherein, output layer neuron
Threshold θ, input layer to the connection weight ω between hidden layer neuronij, hidden layer neuron to output layer neuron
Between connection weight ωj。
10. according to the method for claim 8, it is characterised in that according to formulaCalculate hidden layer the
The input signal net of j neuron nodej；According to formulaCalculate hidden layer jth
The output signal o of individual neurodej；According to formula：Meter
Calculate the input signal net of output layer neuron node；According to formula
The output signal y of output layer neurode is calculated, the regulation and control of the ignition timing to hcci engine are realized by output vector.
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Cited By (4)
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| CN109466375A (en) * | 2018-12-05 | 2019-03-15 | 北京车和家信息技术有限公司 | Distance increasing unit control method and equipment, computer readable storage medium, vehicle |
| CN112963256A (en) * | 2021-03-22 | 2021-06-15 | 重庆邮电大学 | HCCI/SI combustion mode switching process control method |
| CN114030461A (en) * | 2021-11-26 | 2022-02-11 | 深圳技术大学 | Hybrid vehicle energy management method and device based on dual-mode engine |
| US11459962B2 (en) * | 2020-03-02 | 2022-10-04 | Sparkcognitton, Inc. | Electronic valve control |
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