CN110356396A - A method of considering the electric car speed instantaneous optimization of road grade - Google Patents
A method of considering the electric car speed instantaneous optimization of road grade Download PDFInfo
- Publication number
- CN110356396A CN110356396A CN201910615009.6A CN201910615009A CN110356396A CN 110356396 A CN110356396 A CN 110356396A CN 201910615009 A CN201910615009 A CN 201910615009A CN 110356396 A CN110356396 A CN 110356396A
- Authority
- CN
- China
- Prior art keywords
- speed
- road
- vehicle
- max
- electric car
- 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
Links
- 238000000034 method Methods 0.000 title claims abstract description 21
- 238000005457 optimization Methods 0.000 title claims abstract description 16
- 238000005265 energy consumption Methods 0.000 claims abstract description 13
- 238000006243 chemical reaction Methods 0.000 claims description 20
- 230000001133 acceleration Effects 0.000 claims description 9
- 238000004364 calculation method Methods 0.000 claims description 5
- 230000005484 gravity Effects 0.000 claims description 4
- 238000005096 rolling process Methods 0.000 claims description 3
- 238000001228 spectrum Methods 0.000 description 3
- 238000007630 basic procedure Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000000446 fuel Substances 0.000 description 2
- 230000001172 regenerating effect Effects 0.000 description 2
- 230000007812 deficiency Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000004146 energy storage Methods 0.000 description 1
- 230000003137 locomotive effect Effects 0.000 description 1
Classifications
-
- 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
- B60W30/00—Purposes of road vehicle drive control systems not related to the control of a particular sub-unit, e.g. of systems using conjoint control of vehicle sub-units
- B60W30/14—Adaptive cruise control
- B60W30/143—Speed control
-
- 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
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/10—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to vehicle motion
- B60W40/105—Speed
-
- 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
- B60W2510/08—Electric propulsion units
- B60W2510/083—Torque
-
- 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
-
- 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
- B60W2520/00—Input parameters relating to overall vehicle dynamics
- B60W2520/10—Longitudinal speed
-
- 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
- B60W2552/00—Input parameters relating to infrastructure
- B60W2552/15—Road slope, i.e. the inclination of a road segment in the longitudinal direction
-
- 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
- B60W2555/00—Input parameters relating to exterior conditions, not covered by groups B60W2552/00, B60W2554/00
- B60W2555/60—Traffic rules, e.g. speed limits or right of way
-
- 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
- Y02T10/80—Technologies aiming to reduce greenhouse gasses emissions common to all road transportation technologies
- Y02T10/84—Data processing systems or methods, management, administration
Landscapes
- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Transportation (AREA)
- Mechanical Engineering (AREA)
- Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Electric Propulsion And Braking For Vehicles (AREA)
Abstract
A kind of method that the present invention proposes electric car speed instantaneous optimization for considering road grade minimizes total power consumption moment, to optimize tractive force or braking moment by converting Equivalent energy consumption for vehicle energy.Furthermore, a kind of speed correlation factor has also been devised to adjust the speed within the scope of given cruising speed, the drawbacks of conventional speed optimization method will obtain future trajectory information in advance is overcome, while this method has extremely short operation time, therefore has extremely strong real vehicle application prospect.
Description
Technical field
The present invention relates to a kind of methods of electric car speed instantaneous optimization for considering road grade, belong to electric car energy
Measure optimisation technique field.
Background technique
Nowadays, a large amount of surface car has had resulted in considerable ecology, society and economic cost.But due to fuel energy
The limited and strategy of sustainable development is laid in source, and countries in the world government is proposed stringent fuel economy and discharge standard.For
Meet increasingly strict regulation, automaker develops technology, such as auto electric, to reduce energy consumption and vehicle
Discharge.
Electric car is one of technology developed in recent years, other than increasing battery size to improve mileage travelled,
Researcher is investigated the energy management system by optimizing electric car to improve the energy efficiency of electric car.Research
Which can be roughly divided into two types for method: (1) reconstructing power system of electric automobile, improve efficiency of energy utilization.For example, four-wheel independently drives
Dynamic (4WID) electric car is realized by hub motor (IWMs), it is advantageously possible for the raising of high-performance and energy efficiency；(2) optimize
Longitudinal direction of car dynamics, i.e. normal-moveout spectrum can realize economical cruise strategy in landform.But most of car speed optimizations are all
Change in road slope is not accounted for.However, change in road slope is implicitly present in real world.Due to overcoming the energy of gravity
It consumes, there are notable differences for the optimal speed spectrum under different gradient.The ecology cruise strategy study of different gradient is also not quite similar.
All there is more or less deficiencies for most of economical cruise strategy at present, if Dynamic Programming (DP) is as a kind of
Globally optimal solution numerically obtains most energy-efficient normal-moveout spectrum.The optimality for the velocity profile that DP method can guarantee,
But it is computationally intensive, it is only applicable to off-line operation.Pontryagins minimal principle (PMP) is to solve for the another kind of optimization problem
Effective ways.Its calculating speed ratio DP is fast, but due to the simplification of Controlling model, energy-optimised performance can be reduced.In addition, PMP
Calculated performance it is also improper in real-time implementation.Furthermore they are substantially based on diesel locomotive, to consideration regenerative braking
The research of electric car is not yet unfolded, while these methods are computationally intensive, it is difficult to be applied in real-time controller.
Summary of the invention
Goal of the invention: it is an object of the invention to solve existing electric car power supply planing method or computationally intensive,
It is only applicable to off-line operation or the simplification due to Controlling model, energy-optimised performance can reduce or to consideration regenerative braking
The research of electric car be not yet unfolded, while these methods are computationally intensive, it is difficult to be applied to the problems in real-time controller.
Technical solution: to solve the above-mentioned problems, the present invention provides technical solution:
A method of considering the electric car speed instantaneous optimization of road grade, comprising the following steps:
Step 1: initial information obtains, and based on road speed limitation and road real-time condition, obtains vehicle initial velocity
And the present road gradient；
Step 2: battery power consumption calculates, and is obtained according to initial information as a result, real-time battery power consumption；
Step 3: kinetic energy conversion speed correlation factor calculates, dynamic according to initial information and road speeds limitation range computation
It can conversion speed correlation factor；
Step 4: overall energy consumption minimizes, and using kinetic energy conversion factor, the kinetic energy change of vehicle can be equivalent to power consumption.
Further, the road information in step 1 obtains mainly by GIS, and road speed restricted information obtains mainly
It is obtained by GPS.
Further, step 2 battery power consumption calculates, and is mainly obtained by longitudinal direction of car dynamics formula, specific formula is such as
Under:
In formula, PeIt is the power of battery,It is battery efficiency, v is vehicle current vehicle speed, and θ is the gradient, Fγ, Fω, Fθ, FαPoint
Not Wei rolling resistance, air drag, grade resistance and acceleration resistance suffered by vehicle, g is acceleration of gravity, and m is complete vehicle quality,
Cγ,Cω,,ρα,Af, a is respectively to roll coefficient, coefficient of air resistance, atmospheric density, front windshield area and vehicle to work as preacceleration.
Further, kinetic energy conversion speed correlation factor ω described in step 3 is calculated, calculation method such as following formula,
Wherein, Pv is with speed dynamic change, vLAnd vHIt is the lower and upper limit of road speed restrictive block, v is that vehicle is currently fast
Degree, β, P0It is the adjustable parameter for ω, range is as follows:
0.5 < P0< 1
β≥1。
Further, overall energy consumption described in step 4 minimizes, calculation method such as following formula,
In formula, EeRepresent electric quantity consumption, TmFor Motor torque, EkFor vehicle energy, in addition, relevant restriction on the parameters is as follows:
Tmin(ωm)≤Tm(t)≤Tmax(ωm)
vmin≤v(t)≤vmax
vmin=vroad_min
vmax=min (vv_max,vroad_max)
a(t)≤alimit
Wherein, vmin, vmaxIt is the lower and upper limit of cruising speed, lower limit vminThe as minimum speed limit of road, the upper limit
vmaxFor road speed limit maximum value vroad_maxWith speed vv_maxThe minimum value of the two, Tmin, TmaxFor the minimal torque and most of motor
Large torque, alimitFor the peak acceleration of vehicle.
The utility model has the advantages that the present invention is compared with prior art:
1, electric car overall energy consumption is reduced, and capacity usage ratio is higher；
2, in the entire control of electric car, electric efficiency gets a promotion, and more work are in high efficiency region；
3, innovatively propose that kinetic energy conversion speed correlation factor, calculation amount are reduced, can carry out online real vehicle makes
With.
Detailed description of the invention
The electric car speed instantaneous optimization method basic procedure of the considerations of Fig. 1 is embodiment of the present invention road grade；
Fig. 2 is the variation tendency of the kinetic energy conversion speed correlation factor of the embodiment of the present invention；
Fig. 3 is (β, P of the embodiment of the present invention0) influence of the adjustable parameter to kinetic energy conversion speed conversion factor ω.
Specific embodiment
The present invention will be further explained below with reference to the attached drawings:
Fig. 1 is the electric car speed instantaneous optimization method basic procedure for considering road grade, and basic ideas are to obtain
By way of on the basis of road current hill grade and vehicle current vehicle speed, by kinetic energy conversion speed correlation factor, automobile kinetic energy is become
Change and turn to be equivalent to power consumption, by being minimized to vehicle total energy consumption, to obtain vehicle optimum control rule.
The first step, initial information obtain: based on road speed limitation and road real-time condition, obtaining vehicle initial velocity
And the present road gradient.
Second step, battery power consumption calculate, and are obtained according to initial information as a result, real-time battery power consumption.
Batteries of electric automobile energy consumption is obtained by longitudinal direction of car dynamics formula, specific formula is as follows:
In formula, PeIt is the power of battery,It is battery efficiency, v is vehicle current vehicle speed, and θ is the gradient, Fγ, Fω, Fθ, FαPoint
Not Wei rolling resistance, air drag, grade resistance and acceleration resistance suffered by vehicle, g is acceleration of gravity, and m is complete vehicle quality,
Cγ,Cω,,ρα,Af, a is respectively to roll coefficient, coefficient of air resistance, atmospheric density, front windshield area and vehicle currently to add
Speed.
Third step, kinetic energy conversion speed correlation factor calculate, and limit range computation according to initial information and road speeds
Kinetic energy conversion speed correlation factor.
The core of the kinetic energy conversion speed conversion factor ω is that specific table is constructed between current vehicle speed and cruising speed
It is acquired up to formula, when car speed height, the kinetic energy of vehicle accumulates the weight for having expired, therefore having reduced kinetic energy, to promote positive kinetic energy to convert
Alternative electric energy consumption.When car speed is lower, the kinetic energy storage of vehicle is poor, therefore increases the weight of kinetic energy, passes through raising
Motor exports to increase the storage of kinetic energy, and weight here is kinetic energy conversion speed conversion factor ω,
Shown in the formula specific as follows of ω:
Wherein, Pv is with speed dynamic change, vLAnd vHIt is the lower and upper limit of road speed restrictive block, v is that vehicle is currently fast
Degree, β, P0It is the adjustable parameter for ω.
Fig. 2 presents kinetic energy conversion speed conversion factor ω with changes in vehicle speed trend, meets and sets expected from vehicle
Effect is counted, when car speed is higher, ω is smaller, on the contrary.
4th step, overall energy consumption minimize, and using kinetic energy conversion factor, the kinetic energy change of vehicle can be equivalent to electric energy and disappear
Consumption.By being minimized to vehicle total energy consumption, available optimum control rule.
The total energy is minimized by what the following cost function of optimization obtained,
In formula, EeRepresent electric quantity consumption, TmFor Motor torque, EkFor vehicle energy.
Wherein, as follows according to vehicle structure feature and driver comfort requirement, relevant parameter constraint:
Tmin(ωm)≤Tm(t)≤Tmax(ωm) (5)
vmin≤v(t)≤vmax (6)
vmin=vroad_min (7)
vmax=min (vv_max,vroad_max) (8)
a(t)≤alimit (9)
Wherein, vmin, vmaxIt is the lower and upper limit of cruising speed, lower limit vminThe as minimum speed limit of road, the upper limit
vmaxFor road speed limit maximum value vroad_maxWith speed vv_maxThe minimum value of the two, Tmin, TmaxFor the minimal torque and most of motor
Large torque, alimitFor the peak acceleration of vehicle.
Fig. 3 illustrates (β, the P of embodiment0) influence of the adjustable parameter to kinetic energy conversion speed conversion factor ω, wherein
0.5 < P0< 1 (10)
β≥1 (11)
Fig. 3 (a) figure presents adjustable parameter P in embodiment0Influence to kinetic energy conversion speed conversion factor ω, with P0
Become larger, the variation tendency of kinetic energy conversion speed conversion factor ω is more obvious, but general trend is roughly the same.
Fig. 3 (b) figure presents adjustable parameter P in embodiment0Influence to kinetic energy conversion speed conversion factor ω, with β
Become larger, the variation tendency of kinetic energy conversion speed conversion factor ω is more obvious, but general trend is roughly the same.
Claims (5)
1. a kind of method for the electric car speed instantaneous optimization for considering road grade, it is characterised in that: the following steps are included:
Step 1: initial information obtain, based on road speed limitation and road real-time condition, obtain vehicle initial velocity and
The present road gradient；
Step 2: battery power consumption calculates, and is obtained according to initial information as a result, calculating real-time battery power consumption；
Step 3: kinetic energy conversion speed correlation factor calculates, and is turned according to initial information and road speeds limitation range computation kinetic energy
Throw-over degree correlation factor；
Step 4: overall energy consumption minimizes, and using kinetic energy conversion speed correlation factor, the kinetic energy change of vehicle can be equivalent to electric energy
Consumption.
2. the method for the electric car speed instantaneous optimization according to claim 1 for considering road grade, it is characterised in that:
Road information in step 1 obtains mainly by GIS, and road speed restricted information is obtained and mainly obtained by GPS.
3. the method for the electric car speed instantaneous optimization according to claim 1 for considering road grade, it is characterised in that:
Step 2 battery power consumption calculates, and is mainly obtained by longitudinal direction of car dynamics formula, specific formula is as follows:
In formula, PeIt is the power of battery,It is battery efficiency, v is vehicle current vehicle speed, and θ is the gradient, Fγ, Fω, Fθ, FαRespectively
Rolling resistance, air drag suffered by vehicle, grade resistance and acceleration resistance, g are acceleration of gravity, and m is complete vehicle quality, Cγ, Cω,
ρα, Af, a is respectively to roll coefficient, coefficient of air resistance, atmospheric density, front windshield area and vehicle to work as preacceleration.
4. the method for the electric car speed instantaneous optimization according to claim 1 for considering road grade, it is characterised in that:
Kinetic energy conversion speed correlation factor ω described in step 3 is calculated, calculation method such as following formula,
Wherein, Pv is with speed dynamic change, vLAnd vHIt is the lower and upper limit of road speed restrictive block, v is vehicle present speed, β,
P0It is the adjustable parameter for ω, range is as follows:
0.5 < P0< 1
β≥1。
5. the method for the electric car speed instantaneous optimization according to claim 1 for considering road grade, it is characterised in that:
Overall energy consumption described in step 4 minimizes, calculation method such as following formula,
In formula, EeRepresent electric quantity consumption, TmFor Motor torque, EkFor vehicle energy, in addition, relevant restriction on the parameters is as follows:
Tmin(ωm)≤Tm(t)≤Tmax(ωm)
vmin≤v(t)≤vmax
vmin=vroad_min
vmax=min (vv_max, vroad_max)
a(t)≤alimit
Wherein, vmin, vmaxIt is the lower and upper limit of cruising speed, lower limit vminThe as minimum speed limit of road, upper limit vmax
For road speed limit maximum value vroad_maxWith speed vv_maxThe minimum value of the two, Tmin, TmaxFor the minimal torque and maximum torsion of motor
Square, alimitFor the peak acceleration of vehicle.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910615009.6A CN110356396B (en) | 2019-07-09 | 2019-07-09 | Method for instantaneously optimizing speed of electric vehicle by considering road gradient |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910615009.6A CN110356396B (en) | 2019-07-09 | 2019-07-09 | Method for instantaneously optimizing speed of electric vehicle by considering road gradient |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110356396A true CN110356396A (en) | 2019-10-22 |
| CN110356396B CN110356396B (en) | 2020-07-31 |
Family
ID=68218614
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910615009.6A Active CN110356396B (en) | 2019-07-09 | 2019-07-09 | Method for instantaneously optimizing speed of electric vehicle by considering road gradient |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110356396B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111275987A (en) * | 2020-01-21 | 2020-06-12 | 东南大学 | Automobile driving speed optimization method considering intersection queue influence |
| CN112061106A (en) * | 2020-09-15 | 2020-12-11 | 中国第一汽车股份有限公司 | Automatic driving control method, device, vehicle and storage medium |
| CN114379381A (en) * | 2022-03-24 | 2022-04-22 | 武汉理工大学 | Electric vehicle ramp driving speed optimization method based on 5G technology |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102180169A (en) * | 2011-04-15 | 2011-09-14 | 合肥工业大学 | Cost based method for optimizing external PHEV (Plug-in Hybrid Electric Vehicle) power assembly and application thereof |
| US20140005879A1 (en) * | 2010-12-17 | 2014-01-02 | Robert Bosch Gmbh | Method and device for determining a range of a vehicle |
| CN105046050A (en) * | 2015-06-18 | 2015-11-11 | 陕西法士特齿轮有限责任公司 | Automobile dynamics based dynamic slope calculating method |
| CN107097791A (en) * | 2017-03-03 | 2017-08-29 | 武汉理工大学 | Four-wheel driven electric vehicle speed-optimization control method based on road grade and curvature |
| CN108216250A (en) * | 2018-01-10 | 2018-06-29 | 吉林大学 | Four-drive electric car speed and road grade method of estimation based on state observer |
| CN108438003A (en) * | 2018-01-05 | 2018-08-24 | 吉林大学 | A kind of hierarchical control method of road vehicle speed-optimization |
| CN108806021A (en) * | 2018-06-12 | 2018-11-13 | 重庆大学 | Electric vehicle target road section energy consumption prediction technique based on physical model and roadway characteristic parameter |
| CN109117438A (en) * | 2017-06-23 | 2019-01-01 | 蔚来汽车有限公司 | Vehicles remaining mileage evaluation method and device with power supply system |
| CN109760668A (en) * | 2019-03-01 | 2019-05-17 | 北华大学 | A kind of vehicle hybrid driving control system and control method based on car networking |
-
2019
- 2019-07-09 CN CN201910615009.6A patent/CN110356396B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140005879A1 (en) * | 2010-12-17 | 2014-01-02 | Robert Bosch Gmbh | Method and device for determining a range of a vehicle |
| CN102180169A (en) * | 2011-04-15 | 2011-09-14 | 合肥工业大学 | Cost based method for optimizing external PHEV (Plug-in Hybrid Electric Vehicle) power assembly and application thereof |
| CN105046050A (en) * | 2015-06-18 | 2015-11-11 | 陕西法士特齿轮有限责任公司 | Automobile dynamics based dynamic slope calculating method |
| CN107097791A (en) * | 2017-03-03 | 2017-08-29 | 武汉理工大学 | Four-wheel driven electric vehicle speed-optimization control method based on road grade and curvature |
| CN109117438A (en) * | 2017-06-23 | 2019-01-01 | 蔚来汽车有限公司 | Vehicles remaining mileage evaluation method and device with power supply system |
| CN108438003A (en) * | 2018-01-05 | 2018-08-24 | 吉林大学 | A kind of hierarchical control method of road vehicle speed-optimization |
| CN108216250A (en) * | 2018-01-10 | 2018-06-29 | 吉林大学 | Four-drive electric car speed and road grade method of estimation based on state observer |
| CN108806021A (en) * | 2018-06-12 | 2018-11-13 | 重庆大学 | Electric vehicle target road section energy consumption prediction technique based on physical model and roadway characteristic parameter |
| CN109760668A (en) * | 2019-03-01 | 2019-05-17 | 北华大学 | A kind of vehicle hybrid driving control system and control method based on car networking |
Non-Patent Citations (1)
| Title |
|---|
| 殷国栋，李广民等: "四轮驱动电动汽车多Agent能量管理体系研究", 《中国机械工程》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111275987A (en) * | 2020-01-21 | 2020-06-12 | 东南大学 | Automobile driving speed optimization method considering intersection queue influence |
| CN112061106A (en) * | 2020-09-15 | 2020-12-11 | 中国第一汽车股份有限公司 | Automatic driving control method, device, vehicle and storage medium |
| CN114379381A (en) * | 2022-03-24 | 2022-04-22 | 武汉理工大学 | Electric vehicle ramp driving speed optimization method based on 5G technology |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110356396B (en) | 2020-07-31 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US8996218B2 (en) | Hybrid drive control device | |
| CN109703375B (en) | Electric automobile regenerative braking energy coordinated recovery control method | |
| CN110356396A (en) | A method of considering the electric car speed instantaneous optimization of road grade | |
| CN113085860B (en) | Energy management method of fuel cell hybrid electric vehicle in following environment | |
| CN110356397B (en) | Hybrid electric vehicle optimization method based on energy normalization minimization of road gradient | |
| CN105857312B (en) | A kind of highway heavy truck speed travels optimization method | |
| CN107065550A (en) | The stroke-increasing electric automobile efficiency optimization control method calculated based on threshold power | |
| CN112046486A (en) | Fuel cell automobile output power correction method, system and storage medium | |
| CN104477051B (en) | A kind of double drive axle bi-motor pure electric vehicle driving motor difference power alienation matching process | |
| Zhang et al. | Regenerative braking for electric vehicle based on fuzzy logic control strategy | |
| CN107458369A (en) | A kind of coaxial parallel-connection formula Energy Distribution in Hybrid Electric Vehicles management method | |
| WO2023098465A1 (en) | Braking and gear shifting control method and system for electric vehicle | |
| CN108215747B (en) | The torque optimization method of bi-motor arrangement and convex optimized algorithm based on pure electric automobile | |
| CN108313057B (en) | Pure electric automobile self-adapting cruise control method based on MPC and convex optimized algorithm | |
| Zhang et al. | Powertrain design and energy management of a novel coaxial series-parallel plug-in hybrid electric vehicle | |
| CN115214608A (en) | Energy output control method and system for extended-range electric transmission mining truck | |
| CN109703593B (en) | Comprehensive optimization method for whole-district operation of contact-net-free tramcar | |
| CN105774797B (en) | Self-adaptive control method for plug-in type parallel hybrid electric vehicle | |
| CN201677876U (en) | Hybrid four-wheel type electric drive system for vehicles | |
| Zhe et al. | A control strategy of regenerative braking system for intelligent vehicle | |
| Mei et al. | A fuzzy sliding-mode control for regenerative braking system of electric vehicle | |
| CN105620262A (en) | Fuel cell and hydraulic pressure hybrid power system and control method thereof | |
| Cai et al. | Study on the control strategy of hybrid electric vehicle regenerative braking | |
| Tan et al. | An Efficiency-Based Hybrid Mode Selection Model for A P134 Plug-In Hybrid Powertrain Architecture | |
| Qu et al. | Instantaneous velocity optimization strategy of electric vehicle considering varying road slopes |
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 |