CN111783228B - Energy-saving-oriented parameter matching optimization method for three-gear speed change system of pure electric vehicle - Google Patents
Energy-saving-oriented parameter matching optimization method for three-gear speed change system of pure electric vehicle Download PDFInfo
- Publication number
- CN111783228B CN111783228B CN202010627960.6A CN202010627960A CN111783228B CN 111783228 B CN111783228 B CN 111783228B CN 202010627960 A CN202010627960 A CN 202010627960A CN 111783228 B CN111783228 B CN 111783228B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- pure electric
- change system
- speed change
- electric vehicle
- 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.)
- Active
Links
- 230000008859 change Effects 0.000 title claims abstract description 46
- 238000005457 optimization Methods 0.000 title claims abstract description 41
- 238000000034 method Methods 0.000 title claims description 14
- 230000001133 acceleration Effects 0.000 claims abstract description 21
- 238000005265 energy consumption Methods 0.000 claims abstract description 18
- 230000005484 gravity Effects 0.000 claims abstract description 6
- 230000005540 biological transmission Effects 0.000 claims description 14
- 230000008569 process Effects 0.000 claims description 6
- 230000009194 climbing Effects 0.000 claims description 5
- 230000009467 reduction Effects 0.000 claims description 4
- 238000005096 rolling process Methods 0.000 claims description 2
- 238000010845 search algorithm Methods 0.000 abstract description 4
- 238000004088 simulation Methods 0.000 description 13
- 238000011160 research Methods 0.000 description 3
- 230000004075 alteration Effects 0.000 description 2
- 238000006467 substitution reaction Methods 0.000 description 2
- 235000006679 Mentha X verticillata Nutrition 0.000 description 1
- 235000002899 Mentha suaveolens Nutrition 0.000 description 1
- 235000001636 Mentha x rotundifolia Nutrition 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000003638 chemical reducing agent Substances 0.000 description 1
- 238000004134 energy conservation Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000002035 prolonged effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/15—Vehicle, aircraft or watercraft design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/17—Mechanical parametric or variational design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2111/00—Details relating to CAD techniques
- G06F2111/04—Constraint-based CAD
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/14—Force analysis or force optimisation, e.g. static or dynamic forces
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
Abstract
Firstly, based on the structural characteristics of a three-gear speed change system of a pure electric logistics vehicle, the parameters of a driving motor and the speed change system are primarily matched according to the power performance index of the pure electric logistics vehicle; then establishing an optimization model which takes acceleration time of 0-50km/h of the vehicle and specific energy consumption of a CHTC-LT circulation working condition as optimization targets and takes driving motor parameters and speed change system parameters as variables, and solving the optimization model based on a Hierarchical Gravity Search Algorithm (HGSA); provides a new idea for improving the dynamic property and the economical efficiency of the vehicle.
Description
Technical Field
The invention relates to the technical field of new energy automobile power systems, in particular to an energy-saving-oriented parameter matching optimization method for a three-gear speed change system of a pure electric vehicle.
Background
The advantages of zero emission, low noise and great energy saving and environmental protection potential of the pure electric vehicle are paid great attention to, and along with the development of logistics industry, the pure electric vehicle has been gradually applied to replace the traditional logistics vehicle so as to reduce the transportation cost. Most of the existing pure electric vehicles in the market adopt fixed speed ratio reducers, and the requirements of vehicles on dynamic property and economy cannot be well met. The working state of the driving motor can be adjusted by using the multi-gear transmission, the performance of the vehicle can be improved, and the performance requirement on the driving motor is reduced.
On the one hand, the prior researches optimize the transmission ratio of the speed change system, do not fully consider the influence of the driving motor parameters on the vehicle performance, and on the other hand, the researches develop the transmission ratio of the speed change system under different motor schemes. The performance of the vehicle is determined by the driving motor and the speed change system, and the influence of any element on the performance of the vehicle is not ignored, so that the driving motor parameter and the speed change system parameter are simultaneously optimized and the optimal parameter is sought, and the method has important significance in improving the power performance of the vehicle and prolonging the endurance mileage of the vehicle.
Disclosure of Invention
The invention aims to research the parameter matching optimization of the three-gear speed change system of the pure electric vehicle, obtain the optimized speed change system parameter and realize the comprehensive improvement of the dynamic property and the economical efficiency of the vehicle.
The technical scheme adopted for realizing the aim of the invention is that the energy-saving-oriented parameter matching optimization method of the three-gear speed change system of the pure electric vehicle comprises the following steps:
step 1: structural design is carried out on a three-gear speed change system of the pure electric vehicle;
step 2: based on the structural characteristics of the three-gear speed change system of the pure electric vehicle in the step 1, the parameters of the three-gear speed change system are primarily matched;
step 3: taking the acceleration time of 0-50km/h of the vehicle and the specific energy consumption of the vehicle when the vehicle runs under the CHTC-LT circulating working condition as optimization targets, taking the driving motor parameters and the speed change system parameters as variables, and establishing an optimization model comprehensively considering the dynamic property and the economical efficiency;
step 4: and (3) solving a multi-objective optimization model of the energy-saving-oriented three-gear speed change system of the pure electric vehicle in the step (3) by adopting an optimization algorithm to obtain optimal driving motor parameters and speed change system parameters.
Preferably, in the step 3, the modeling process for optimizing the parameter matching of the three-gear speed change system of the pure electric logistics vehicle by comprehensively considering the dynamic property and the economy of the pure electric logistics vehicle is as follows:
1. optimization objective
In the preliminary matching process of the power system, the peak power and the maximum transmission ratio of the driving motor are mainly determined by the index requirement of the acceleration time of 0-50km/h of the vehicle, and the maximum climbing gradient of the vehicle is also determined by the acceleration performance of the vehicle. Therefore, the maximum climbing gradient and the maximum vehicle speed of the vehicle can be used as constraint conditions to be processed, and the specific energy consumption of the vehicle when the vehicle runs under the CHTC-LT circulation working condition and the acceleration time of 0-50km/h of the vehicle are selected as optimization targets.
(1) Acceleration time of 0-50km/h
The maximum driving force on wheels obtained by the vehicle and the running resistance of the vehicle are main factors influencing the acceleration time of 0-50km/h of the pure electric logistics vehicle.
Wherein t is a Acceleration time of 0-50km/h, m 0 For empty mass of vehicle, m c For loading weight, v s1 Upshift vehicle speed of 1-2 gear, v s2 Upshift speed of 2-3 gear, F t1 Is 0 to t 1 Period vehicle driving force, F t2 At t 1 To t 2 Period vehicle driving force, F b Resistance to vehicle travel, v max For maximum speed of vehicle, delta 1 、δ 2 、δ 3 The equivalent mass inertia coefficients of the three phases of the vehicle are respectively.
(2) Specific energy consumption under circulation condition
The mass of the whole pure electric logistics vehicle studied in the text is 4495kg, so that the CHTC-LT driving cycle working condition in the novel national standard CATC cycle working condition is selected as the driving cycle working condition of the pure electric logistics vehicle. The specific energy consumption in the circulation working condition is used as an index for measuring the economic performance of the vehicle, and represents the energy consumed by the running unit mileage (km) of the vehicle under the CHTC-LT working condition, wherein the unit is kW.h/km. Specific energy consumption under the circulation working condition is as follows:
wherein, E C For the specific energy consumption of the circulation working condition, m is the whole vehicle mass of the pure electric vehicle, g is the gravity acceleration, f is the rolling resistance coefficient of the vehicle, beta is the ramp angle of the driving road, C D The wind resistance coefficient of the pure electric vehicle is that A is the windward area of the pure electric vehicle, delta is the equivalent mass inertia coefficient of the pure electric vehicle, t is time variable, rho is air density, and the air density under standard atmospheric pressure takes the value of rho= 1.2258 N.S 2 ·m -4 ，L C For the total driving distance of the CHTC-LT circulation working condition, v (t) is the speed of the pure electric vehicle at the moment t, F (t) is the driving force provided by the power assembly during the driving process of the vehicle, eta T For transmission efficiency eta M And (t) is the efficiency of the driving motor at the time t, and is calculated as follows:
wherein P is i To drive the output power of a certain working point of the motor, P Cu Copper loss, P, at the operating point for driving the motor e Is eddy current loss, P h Is hysteresis loss, P m For mechanical loss, P max To drive the peak power of the motor, P N To rated power of the driving motor, n i To drive the motor speed, n N For the rated rotational speed of the drive motor, n e Is the rated rotation speed of the driving motor.
2. Optimizing variables
The peak power, rated rotation speed and rated power of the driving motor jointly influence the efficiency of the driving motor at each working point. Different transmission ratios and peak torque of a driving motor can influence the driving force output by the power assembly under each gear, so that the power performance of the vehicle is influenced; the coordination matching of the speed change system parameters and the driving motor parameters can enable the vehicle to obtain good power performance, meanwhile, the driving motor can work in a high-efficiency area more, the energy efficiency of the whole vehicle is improved, the endurance mileage of the electric logistics vehicle is prolonged, and the transportation cost of the electric logistics vehicle is reduced.
The increase of the peak power of the driving motor and the maximum rotating speed of the motor can lead to the increase of the cost of the driving motor, so the invention uses the rated power P of the driving motor under the premise of not changing the peak power and the maximum rotating speed of the driving motor N Drive rated rotation speed n N Three-gear reduction ratio i of speed change system 3 And the characteristic parameter alpha of the NGW planetary gear train is taken as an optimization variable. Namely:
X＝[X 1 ,X 2 ,X 3 ,X 4 ]＝[P N ,n N ,i 3 ,α]
3. constraint conditions
(1) Maximum climbing constraint
The driving force transmitted to the wheels by the power assembly needs to be larger than the resistance of the vehicle when the vehicle runs at the climbing speed, namely:
wherein T is max To drive the peak torque of the motor beta max I is the maximum ramp angle of the driving road 1 And r is the radius of the wheel for the first gear reduction ratio of the speed change system.
(2) Maximum vehicle speed constraint
When the pure electric logistics vehicle runs on a horizontal windless road surface, the peak power of the driving motor needs to meet the requirement on the output power of the driving motor when the vehicle runs at the highest speed, and in order to ensure that the vehicle runs at the required highest speed, the highest gear transmission ratio of the speed change system needs to meet the constraint:
wherein n is max The maximum rotation speed of the driving motor is set.
(3) Wheel slip restraint
The vehicle studied in the invention is a rear-drive vehicle, and in the starting and sudden acceleration stage of the vehicle, in order to prevent the wheel slip and improve the stability of the vehicle, the maximum torque transmitted to the wheel is limited:
wherein mu is the wheel slip coefficient, and the maximum value is 1.02; l is the wheelbase of front and rear axles of the pure electric vehicle, and 3308mm is taken; l (L) 1 Taking 2105mm for the distance from the mass center of the pure electric vehicle to the front axle of the vehicle; h is a g The mass center height of the full-load pure electric vehicle is 930mm.
(4) Boundary constraints
The feasible domain of each optimization variable is reduced, the iteration speed of the optimization algorithm can be increased, and the quick solution of the optimization model is facilitated, so that the boundary of each optimization variable is constrained by combining the analysis of the parameter matching process of the pure electric vehicle dynamic system.
20≤P N ≤60
2000≤n N ≤4000
8≤i 3 ≤9.55
1.4≤α≤2
In order to ensure smooth gear shifting during running of the vehicle, the ratio of the transmission ratios of two adjacent gears in the speed change system should be less than 2, i.e. i n /i n+1 ≤2。
The comprehensive performance parameter optimization model is as follows:
minF(P N ,n N ,i 3 ,α)＝(mint a ,minE C )
preferably, in step 4, the optimization model is solved by using a hierarchical gravity search algorithm. Setting each parameter of an algorithm, and setting the dimension d=4 of a solution in a speed change system parameter optimization model, wherein the initial step is thatInitial bottom layer mass point group size n=50, universal gravitation coefficient G 0 The iteration step of the universal gravitation number l=100, and the maximum iteration number t=50. The hierarchical gravity search algorithm flow is shown in fig. 2.
Compared with the optimization technology of the existing electric vehicle speed change system, the invention has the beneficial effects that:
according to the invention, the influence of the transmission ratio of the speed change system and the driving motor parameters on the vehicle performance is comprehensively considered, and the driving motor and the speed change system parameters are primarily matched according to the power performance index of the electric logistics vehicle. And then, taking the acceleration time of 0-50km/h of the vehicle and the specific energy consumption of the CHTC-LT circulation working condition as optimization targets, taking the driving motor parameters and the speed change system parameters as variables, constructing an energy-saving-oriented multi-target matching optimization model of the three-gear speed change system parameters of the pure electric vehicle, and providing a new thought for improving the comprehensive performance of the vehicle. The method for optimizing the parameter matching of the three-gear speed change system of the pure electric vehicle for energy conservation provided by the invention effectively improves the dynamic property and the economical efficiency of the vehicle.
Drawings
FIG. 1 is a flow of optimization method for parameter matching of three-gear speed change system of energy-saving-oriented pure electric vehicle
FIG. 2 hierarchical gravity search algorithm optimization flow
FIG. 3 simulation model of vehicle dynamic performance
FIG. 4 vehicle acceleration time simulation model
FIG. 5 results of dynamic performance simulation
FIG. 6 0-50km/h acceleration simulation results
FIG. 7 whole vehicle simulation model
FIG. 8 CHTC-LT operating mode energy consumption simulation results
Detailed Description
The present invention will be further described with reference to the drawings and examples, but it should not be construed that the scope of the above-described subject matter of the present invention is limited to the following examples. Various substitutions and alterations are made according to the ordinary skill and familiar means of the art without departing from the technical spirit of the invention, and all such substitutions and alterations are intended to be included in the scope of the invention.
In the implementation, a vehicle dynamic performance simulation model and a whole vehicle model are established by utilizing a MATLAB/Simulink simulation platform, simulation analysis and comparison are carried out on the power system parameters before and after optimization based on the optimization results shown in the table 1, and the acceleration time of 0-50km/h and the CHTC-LT cycle working condition energy consumption condition of the vehicle are verified.
Table 1 optimization results
In order to verify the effectiveness of the optimization result, the resistance moment born by the vehicle when the vehicle runs on a flat road and a 30% slope road and the driving moment provided by the power system are analyzed and calculated along with the change of the vehicle speed by combining the optimized power system parameters, and a power performance simulation model shown in fig. 3 and a vehicle 0-50km/h acceleration time simulation model shown in fig. 4 are established. As can be seen from FIG. 5, the highest speed of the vehicle can reach 99.8km/h due to the change of the 3-gear transmission ratio, and compared with the parameter preliminary matching stage, the highest running speed of the vehicle is improved by 5.67 percent; meanwhile, the peak torque of the driving motor and the 1-gear transmission ratio of the speed change system are increased at the same time, so that the maximum starting gradient of the vehicle is greatly improved, the maximum starting gradient is improved from 32.69% to 46.21%, the lifting degree is 41.3%, the peak power of the driving motor is not optimized as a variable, and the vehicle speed of the vehicle running on a 30% gradient road surface is still 19.5km/h due to power limitation. Fig. 6 is a graph comparing acceleration times of 0-50km/h of the optimized front and rear electric vehicle, and it can be seen that the time required for accelerating the optimized front electric vehicle from rest to 50km/h is 8.47s, the acceleration time required for optimizing is 7.92s, and the optimized lifting degree is 6.69%.
And establishing a whole vehicle forward simulation model shown in fig. 7, and calculating the condition that the vehicle energy consumption of the pure electric logistics vehicle changes along with mileage under the CHTC-LT driving cycle working condition. FIG. 8 is a graph showing the comparison of the energy consumption of the CHTC-LT driving cycle conditions of a pure electric vehicle before and after optimization, wherein the energy consumption of the vehicle driving cycle before optimization is 0.4798 kW.h/km, the energy consumption of the vehicle after optimization is 0.4729 kW.h/km, the lifting degree is 1.44%, and the economic performance of the vehicle is improved.
In summary, under the condition that the peak power of the driving motor is fixed, the accelerating time of 0-50km/h of the vehicle can be shortened by 6.69% by increasing the peak torque of the motor and the maximum transmission ratio of the speed change system, and the maximum starting gradient of the vehicle can be improved to a certain extent. Through optimizing driving motor parameters and matching with a multi-gear transmission to adjust the working range of the driving motor, simulation analysis shows that compared with preliminary matching parameters, the specific energy consumption of driving circulation working conditions is reduced by 1.44%, and the energy efficiency of the whole vehicle is improved to a certain extent.
Claims (1)
1. The energy-saving-oriented parameter matching optimization method for the three-gear speed change system of the pure electric vehicle is characterized by comprising the following steps of:
step 1: structural design is carried out on a three-gear speed change system of the pure electric vehicle;
step 2: based on the structural characteristics of the three-gear speed change system of the pure electric vehicle in the step 1, the parameters of the three-gear speed change system are primarily matched;
step 3: taking the acceleration time of 0-50km/h of the vehicle and the specific energy consumption of the vehicle when the vehicle runs under the CHTC-LT circulating working condition as optimization targets, taking the driving motor parameters and the speed change system parameters as variables, and establishing an optimization model comprehensively considering the dynamic property and the economical efficiency;
step 4: solving a multi-objective optimization model of the energy-saving-oriented three-gear speed change system of the pure electric vehicle in the step 3 by adopting an optimization algorithm to obtain optimal driving motor parameters and speed change system parameters;
in step 3, the modeling process is:
(1) Optimization objective
1) Acceleration time of 0-50km/h
Wherein t is a Acceleration time of 0-50km/h, m 0 For empty mass of vehicle, m c For loading weight, v s1 Upshift vehicle speed of 1-2 gear, v s2 Upshift speed of 2-3 gear, F t1 Is 0 to t 1 Period vehicle driving force, F t2 At t 1 To t 2 Period vehicle driving force, F b Resistance to vehicle travel, v max For maximum speed of vehicle, delta 1 、δ 2 、δ 3 Equivalent mass inertia coefficients of three stages of the vehicle respectively;
2) Specific energy consumption under circulation condition
Wherein E is C For the specific energy consumption of the circulation working condition, m is the whole vehicle mass of the pure electric vehicle, g is the gravity acceleration, f is the rolling resistance coefficient of the vehicle, beta is the ramp angle of the driving road, C D The wind resistance coefficient of the pure electric vehicle is that A is the windward area of the pure electric vehicle, delta is the equivalent mass inertia coefficient of the pure electric vehicle, t is time variable, rho is air density, and the air density under standard atmospheric pressure takes the value of rho= 1.2258 N.S 2 ·m -4 ，L C For the total driving distance of the CHTC-LT circulation working condition, v (t) is the speed of the pure electric vehicle at the moment t, F (t) is the driving force provided by the power assembly during the driving process of the vehicle, eta T For transmission efficiency eta M And (t) is the efficiency of the driving motor at the time t, and is calculated as follows:
wherein P is i To drive the output power of a certain working point of the motor, P Cu Copper loss, P, at the operating point for driving the motor e Is eddy current loss, P h Is hysteresis loss, P m For mechanical loss, P max To drive the peak power of the motor, P N To rated power of the driving motor, n i To drive the motor speed, n N For the rated rotational speed of the drive motor, n e Rated rotation speed of the driving motor;
(2) Optimizing variables
At the rated power P of the driving motor N Drive rated rotation speed n N Three-gear reduction ratio i of speed change system 3 As an optimization variable, the characteristic parameter alpha of the NGW planetary gear train is as follows:
X＝[X 1 ,X 2 ,X 3 ,X 4 ]＝[P N ,n N ,i 3 ,α]
(3) Constraint conditions
1) Maximum climbing constraint
Wherein T is max To drive the peak torque of the motor beta max I is the maximum ramp angle of the driving road 1 The speed reduction ratio is the first gear of the speed change system, and r is the radius of the wheel;
2) Maximum vehicle speed constraint
Wherein n is max The maximum rotation speed of the driving motor is set;
3) Wheel slip restraint
Wherein mu is the wheel slip coefficient; l is the wheelbase of front and rear axles of the pure electric vehicle; l (L) 1 The distance from the mass center of the pure electric vehicle to the front axle of the vehicle; h is a g In a full-load state for the pure electric vehicleIs defined by the centroid height of (2);
4) Boundary constraints
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010627960.6A CN111783228B (en) | 2020-07-02 | 2020-07-02 | Energy-saving-oriented parameter matching optimization method for three-gear speed change system of pure electric vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010627960.6A CN111783228B (en) | 2020-07-02 | 2020-07-02 | Energy-saving-oriented parameter matching optimization method for three-gear speed change system of pure electric vehicle |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111783228A CN111783228A (en) | 2020-10-16 |
| CN111783228B true CN111783228B (en) | 2023-10-31 |
Family
ID=72758236
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010627960.6A Active CN111783228B (en) | 2020-07-02 | 2020-07-02 | Energy-saving-oriented parameter matching optimization method for three-gear speed change system of pure electric vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111783228B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114861332B (en) * | 2022-07-05 | 2022-11-18 | 清华大学 | Topological structure and parameter layering optimization method of electric drive system of dual-motor transmission |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105608299A (en) * | 2016-03-04 | 2016-05-25 | 安徽工程大学 | Multi-objective optimization based parameter matching method for power system of battery electric vehicle |
| CN106599439A (en) * | 2016-12-08 | 2017-04-26 | 重庆大学 | Energy consumption-oriented parameter optimization and matching method for dual-motor power system of pure electric vehicle |
| CN108491670A (en) * | 2018-04-17 | 2018-09-04 | 常熟理工学院 | A kind of parameter matching of electronic logistic car driving motor and optimization method |
| CN108984812A (en) * | 2017-06-05 | 2018-12-11 | 湖南科技大学 | A kind of power matching method suitable for small-sized pure electric tractor |
| CN110203075A (en) * | 2019-05-31 | 2019-09-06 | 武汉理工大学 | A kind of four-wheel hub motor Vehicular system power matching method |
| CN110688477A (en) * | 2019-10-10 | 2020-01-14 | 华夏幸福产业投资有限公司 | Prediction method, device, equipment and storage medium in technical hotspot field |
| CN110717218A (en) * | 2019-09-18 | 2020-01-21 | 北京理工大学 | Electric drive vehicle distributed power drive system reconstruction control method and vehicle |
| CN110941875A (en) * | 2019-11-11 | 2020-03-31 | 常熟理工学院 | Full hybrid vehicle energy efficiency optimization control method of adaptive asynchronous particle swarm |
| CN111199311A (en) * | 2019-12-24 | 2020-05-26 | 国网江苏省电力有限公司扬州供电分公司 | Residential area charging facility power optimization method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| AT518850B1 (en) * | 2016-07-13 | 2021-11-15 | Avl List Gmbh | Method for simulation-based analysis of a motor vehicle |
-
2020
- 2020-07-02 CN CN202010627960.6A patent/CN111783228B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105608299A (en) * | 2016-03-04 | 2016-05-25 | 安徽工程大学 | Multi-objective optimization based parameter matching method for power system of battery electric vehicle |
| CN106599439A (en) * | 2016-12-08 | 2017-04-26 | 重庆大学 | Energy consumption-oriented parameter optimization and matching method for dual-motor power system of pure electric vehicle |
| CN108984812A (en) * | 2017-06-05 | 2018-12-11 | 湖南科技大学 | A kind of power matching method suitable for small-sized pure electric tractor |
| CN108491670A (en) * | 2018-04-17 | 2018-09-04 | 常熟理工学院 | A kind of parameter matching of electronic logistic car driving motor and optimization method |
| CN110203075A (en) * | 2019-05-31 | 2019-09-06 | 武汉理工大学 | A kind of four-wheel hub motor Vehicular system power matching method |
| CN110717218A (en) * | 2019-09-18 | 2020-01-21 | 北京理工大学 | Electric drive vehicle distributed power drive system reconstruction control method and vehicle |
| CN110688477A (en) * | 2019-10-10 | 2020-01-14 | 华夏幸福产业投资有限公司 | Prediction method, device, equipment and storage medium in technical hotspot field |
| CN110941875A (en) * | 2019-11-11 | 2020-03-31 | 常熟理工学院 | Full hybrid vehicle energy efficiency optimization control method of adaptive asynchronous particle swarm |
| CN111199311A (en) * | 2019-12-24 | 2020-05-26 | 国网江苏省电力有限公司扬州供电分公司 | Residential area charging facility power optimization method |
Non-Patent Citations (1)
| Title |
|---|
| 李聪波 ; 张弛 ; 屈世阳 ; 胡曾明.考虑道路坡度与车辆载重的纯电动物流车综合性能换挡规律.《中国机械工程》.2021,275-283+289. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111783228A (en) | 2020-10-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Di Nicola et al. | Optimization of a multiple-speed transmission for downsizing the motor of a fully electric vehicle | |
| CN110667395A (en) | Multi-target optimization method for gear shifting rule of pure electric vehicle of two-gear automatic gearbox based on braking working condition | |
| CN110155034B (en) | Matching method for input distribution type hybrid power system planet row characteristic parameters | |
| CN110569527A (en) | automobile transmission ratio design and optimization method based on hybrid particle swarm algorithm | |
| Laitinen et al. | Improving electric vehicle energy efficiency with two-speed gearbox | |
| CN111783228B (en) | Energy-saving-oriented parameter matching optimization method for three-gear speed change system of pure electric vehicle | |
| CN110356396B (en) | Method for instantaneously optimizing speed of electric vehicle by considering road gradient | |
| CN107862325A (en) | One kind is applied to the pure electronic biradical speed motor characteristic parameter matching method of cargo vehicle | |
| CN202448723U (en) | Chassis for pure electric automobile | |
| CN114312330A (en) | Electric automobile brake gear shifting control method and system | |
| Yasin | Modelling and control of hybrid vehicle | |
| Yiangkamolsing et al. | A development of electric Tuk Tuk conversion in Thailand | |
| CN105201663B (en) | A kind of control method for realizing engine optimal economic rotating speed | |
| Gupta et al. | Analysis of variable gear system on energy consumption in electric vehicle using simulation tool | |
| Ruan et al. | Comparing of single reduction and CVT based transmissions on battery electric vehicle | |
| Chaim et al. | A Model of Vehicle Fuel Consumption at conditions of the EUDC | |
| Seal | Viking 23-zero emissions in the city, range and performance on the freeway | |
| CN102673358B (en) | A kind of pure electric automobile chassis | |
| Lai et al. | Design study of parallel HEV drive train with full size engine | |
| Yavuz et al. | Comparison of ideal traction hyperbola curves with Matlab-Simulink in vehicles | |
| Sun et al. | Mathematical Methods Applied to Economy Optimization of an Electric Vehicle with Distributed Power Train System | |
| CN112389211B (en) | Extended range electric vehicle transmission parameter matching and optimizing method | |
| CN104843013A (en) | Efficient gear transmission ratio matching method of car speed changing system | |
| Mahala et al. | Development of transmission specifications for an electric vehicle | |
| Kumar et al. | Design and analysis of a parallel hybrid electric vehicle for Indian conditions |
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 |